Advances in automotive technologies  select proceedings of icpat 2019

Anoop Kumar

Air conditioning systems are crucial for modern vehicles, significantly impacting energy performance due to the power they consume Vapour compression refrigeration systems are commonly employed in warm and humid climates, drawing energy from the vehicle's engine to operate the compressor However, the power consumption of this compressor can be reduced by implementing a hybrid mechanical compression refrigeration system that utilizes waste heat from the vehicle Ejector mechanical compression hybrid refrigeration systems are particularly suitable due to their compact design and ease of operation A hybrid ejector-mechanical air conditioning system has been configured for passenger vehicles, and its thermodynamic analysis has been conducted to evaluate its coefficient of performance.

Keywords Ejector-compression hybrid refrigerationãEjector modelingã System configuration and analysisã COP

Air-conditioning systems are vital in modern vehicles, particularly in hot climates, utilizing vapor compression refrigeration (VCR) for efficient cooling VCR systems are favored for their compact design, reliability, and cost-effectiveness Key components include the compressor, condenser, evaporator, and expansion valve, with the compressor powered by the car's engine However, these air-conditioning systems can negatively affect fuel economy, decreasing conventional vehicle mileage by approximately 1.52 km per liter and impacting high fuel economy vehicles even more severely, with reductions of about 2.74 km per liter.

VIT University, Vellore 632014, India e-mail: anoopkumar.m@vit.ac.in © Springer Nature Singapore Pte Ltd 2021

M R Nalim et al (eds.), Advances in Automotive Technologies, Lecture Notes in Mechanical Engineering, https://doi.org/10.1007/978-981-15-5947-1_2

Conventional air-conditioning systems can significantly diminish the range of electric vehicles and the fuel economy of hybrid electric vehicles by nearly 40%, influenced by the air conditioner's size and driving conditions With the growing awareness of the detrimental effects of emissions from internal combustion engine vehicles, there is an urgent need for more energy-efficient air-conditioning systems in cars Modifying standard vapor compression systems could facilitate energy savings, especially since waste heat from engine cooling water and exhaust gases presents an opportunity for developing a hybrid heat energy system.

Various refrigeration methods utilize input energy in the form of heat, including vapor absorption, thermo-electric, adsorption, and ejector systems Among these, a hybrid ejector system is particularly suitable due to its simplicity, cost-effectiveness, and compact design However, the main drawbacks of ejector refrigeration systems are their low coefficient of performance (COP) and insufficient effectiveness under off-design conditions These limitations can be addressed by configuring a vapor compression-ejector hybrid air-conditioning system specifically for passenger car applications.

2 Air Conditioning System for IC Engine Cars

A car air conditioning (AC) system operates similarly to a domestic AC system but on a smaller scale, utilizing key components like the evaporator and condenser It functions based on the vapor compression refrigeration cycle, where liquid refrigerant evaporates in the evaporator, absorbing latent heat from the air supplied to the car cabin, resulting in cool air For the system to continue producing refrigeration, the vaporized refrigerant must be condensed back into liquid form, which requires rejecting heat to the ambient environment.

Fig 1 Schematic of car AC

A filter drier is essential in car air conditioning systems, as it ensures the refrigerant vapor from the evaporator is pressurized to the saturation pressure that corresponds to the ambient temperature This process is facilitated by a compact refrigerant compressor powered by the engine Typically, car AC compressors are equipped with a clutch connected via a belt drive, allowing for on-off operation to maintain the desired cabin temperature efficiently.

An ejector is a flow device that utilizes nozzle sections to enable a high-pressure primary fluid to draw in a low-pressure secondary fluid, resulting in a mixed flow discharged at an intermediate pressure Functioning similarly to a compressor or pump, the ejector pressurizes fluid flow without the need for moving parts, lubricants, or maintenance The performance of an ejector is primarily defined by two key parameters: the entrainment ratio, which measures the mass flow rates of the secondary and primary fluids, and the pressure lift ratio, indicating the ratio of the ejector's outlet pressure to the secondary flow pressure at the inlet.

A typical ejector geometry consists of four key components The first is the nozzle, which allows the primary fluid to expand and creates a low-pressure area at its outlet, aiding in the entrainment of the secondary flow Next is the suction chamber, where the secondary flow enters the motive flow The third component is the mixing chamber, where the two flows combine, featuring a convergent section and a constant-area section Lastly, the diffuser reduces the velocity of the mixed flow while increasing the pressure to achieve the desired backpressure The geometry of the ejector is primarily characterized by the area ratio, defined as the area of the constant-area section in the mixing chamber divided by the nozzle throat area.

The primary flow serves as the motive fluid for the ejector, while the secondary flow functions as the driven fluid Both flows can exist in various states, including liquid, vapor, or two-phase.

Ejectors play a crucial role in refrigeration systems, primarily in two applications: the ejector refrigeration system (ERS), which utilizes a vapor ejector in place of a compressor, and the ejector-enhanced vapor compression refrigeration system, which can have various configurations A common configuration involves a two-phase ejector serving as the expansion device, optimizing system performance, particularly in trans-critical CO2 refrigeration due to its ability to achieve a significant pressure lift Additionally, hybrid systems that combine ejectors with mechanical compressors are also explored in this literature.

Internal combustion engine (ICE) vehicles generate multiple sources of waste heat, including engine cylinder cooling water and exhaust gases A compact heat exchanger can effectively utilize this waste heat to warm the refrigerant in a hybrid air-conditioning system that combines mechanical compression and ejector technology This system features a mechanical compressor and an ejector arranged in series, allowing the refrigerant from the compressor to be entrained by an ejector powered by motive steam from a heater Consequently, the compressor operates under reduced head pressure, enhancing overall efficiency.

Engine cylinder, 2 Compressor, 3 Condenser, 4 liquid receiver

5 Pump, 6 Heater(Generator), 7 Ejector, 8 Car cabin Evaporator

Fig 4 Hybrid system configuration Condenser

The hybrid system efficiently utilizes waste heat from the engine to maintain hot water temperatures between 80–90 °C, reducing power drain from the engine Liquid refrigerant is pumped to the heater, where it undergoes a phase change to saturated vapor as it passes through a coil This high-pressure vapor is then expanded in the primary nozzle of the ejector, entraining lower-pressure vapor from the compressor The system's design allows the compressor to operate at half the required pressure ratio, optimizing power savings Incorporating electronic pressure and temperature controls ensures the system adapts to ambient conditions, and in case of off-design conditions, the pump ceases operation, transferring the entire load to the mechanical compressor, thus enhancing the reliability of the air-conditioning system.

An analysis of the hybrid vapor compression-ejector system involves evaluating energy and momentum balances across its various components By referencing the accompanying diagram, mathematical equations can be formulated to represent the distinct elements of the system effectively.

The ejector is a critical component in hybrid systems, where the interaction between primary and secondary flows is complex Over the years, researchers have developed effective mathematical models that accurately predict ejector performance, aligning well with experimental data A significant early analysis by Keenan et al (1950) introduced two methods to describe the ejector mixing process: the constant-pressure mixing model, which assumes a constant pressure during mixing, and the constant-area mixing model, which considers mixing occurring in a constant-area section of the ejector.

For modelling the ejector, a constant-pressure mixing theory with the following assumptions is employed.

1 Steady flow the ejector components

2 Refrigerant heat loss in the ejector is negligible

The energy and momentum balance equations for flow through different sections of an ejector can be articulated, highlighting the significance of the entrainment ratio (μ) This key parameter is defined as the ratio of the mass flow rate of the secondary fluid to that of the primary fluid, expressed mathematically as μ = m2/m6.

Applying steady flow energy balance to the primary nozzle flow, the velocity of primary fluid at nozzle exit can be written as

Paul Robertson and Rammohan A

Recent advancements in the automotive industry have significantly transformed vehicle development over the past decade, enabling cars to operate autonomously and greatly enhancing their performance.

As autonomous vehicles represent the future of transportation, they are crucial in the automotive industry's research and development This article discusses a semi-autonomous system designed for small electric vehicles, where certain functions like the clutch, accelerator, and brake operate automatically using ultrasonic sensors to detect obstacles, while gear shifting remains manual The system utilizes a Bajaj CT100 engine, modified transmission, and drum brake, with power transferred to the wheels through this enhanced transmission A Raspberry Pi controller and Python programming are employed to manage the system, enabling it to start and operate based on obstacle proximity detected by the ultrasonic sensor.

Keywords Autonomous transmissionã Gear ãDrums braking systemã Ultrasonic sensor

Research on autonomous vehicles is a key focus for the automotive industry, as they are expected to lead the future of transportation Premium vehicle manufacturers are now equipping their high-end models with advanced features like Automatic Cruise Control (ACC), which allows the vehicle to maintain a safe speed relative to surrounding traffic With ACC activated, drivers can relax their foot from the accelerator and brake, enhancing driving comfort and safety.

Vellore Institute of Technology, Vellore 632014, India e-mail: paulrobert1510@gmail.com

Rammohan A. e-mail: rammohan.a@vit.ac.in © Springer Nature Singapore Pte Ltd 2021

The Adaptive Cruise Control (ACC) system manages vehicle acceleration and maintains a safe distance between vehicles using automatic braking and acceleration This technology is particularly beneficial on highways, alleviating driver fatigue When ACC is activated, the vehicle maintains a steady speed, regardless of traffic conditions However, it is classified as a semi-autonomous system because the driver retains manual control over steering Once the driver engages the brake or accelerator, the system switches back to manual mode, ensuring a seamless driving experience.

The electromagnetic clutch system engages transmission through electronic actuation while mechanically transmitting torque from the engine This system can also assist in vehicle braking by releasing the clutch in lower gears, utilizing engine power to decelerate without locking the wheels, thus improving braking efficiency and stopping distances It consumes electrical energy during engagement and can automatically apply brakes using an IR sensor to detect obstacles when the driver is distracted The braking process involves a pneumatic cylinder that expands the brake shoe, with the braking rate adjustable via a flow control valve Additionally, sensors monitor the automatic transmission system's performance, detecting faults in various components, while a hydraulic pump driven by the engine provides the necessary pressure for gear shifts Researchers have implemented UV sensors for rpm data transmission to control vehicle speed and enhance safety through a braking system that detects pedal pressure Furthermore, an advanced emergency braking system activates based on the distance to obstacles, utilizing a simple chip that integrates GPS and radar signals to optimize braking and acceleration control for pedestrian protection.

An automatic braking system utilizing pneumatic principles effectively employs pressurized air for braking When an obstacle is detected within 4 feet, a switch linked to the bumper activation system is triggered, operational at speeds of 40–50 km/h This system, monitored by a proximity sensor, enhances safety for both pedestrians and vehicles by utilizing compressed air managed through solenoid valves The braking mechanism ensures a smooth deceleration, minimizing risks associated with sudden stops, particularly in rear-approaching scenarios The braking system's efficiency is determined by factors such as vehicle weight, tire specifications, and rim dimensions, which collectively calculate the necessary braking torque Gear shifting is facilitated by a stepper motor, controlled via the steering wheel Additionally, the friction braking system is vital for long-distance braking in high-speed trains, allowing for speed regulation and deceleration prevention This paper discusses a hydro-mechanical automatic transmission gear shifting operation, characterized by precise oil pressure in the clutch cylinder, ensuring error-free shifting without power interruptions The dynamic shifting parameters optimize manpower and time efficiency, while the braking power is activated promptly, considering brake weight The analysis of brake disks, shift gears, and hub sets informs the reduction of system weight in the transmission, enhancing overall performance The automated manual transmission combines manual systems with actuators and hydraulic or electromechanical components, aimed at reducing energy consumption, lowering exhaust emissions, and improving vehicle efficiency.

This proposed work introduces a semi-autonomous transmission and braking system that utilizes sensor data to automatically engage these systems based on real-time requirements By analyzing the distance and speed of nearby obstacles, the system operates the clutch and brake through an electromagnetic clutch and solenoid, allowing for automatic deceleration when obstacles are detected Conversely, when the path is clear, the transmission system is re-engaged to transmit power efficiently The design and validation of this innovative system demonstrate its potential to enhance vehicle safety and performance.

This experiment utilizes key components including the Bajaj CT100 engine and an auto drum braking system, as illustrated in Fig 1 The engine is mounted on a frame and serves multiple functions such as transmission through the clutch, gear, and accelerator, and is primarily started using a kick start mechanism The drum brake system operates based on brake shoes fitted within a drum; when the brake pedal is pressed, hydraulic fluid flows from the master cylinder to the wheel cylinder, pressing the shoe against the drum to apply the brakes Upon releasing the pedal, the brakes disengage, allowing the wheel to rotate freely The assembly of the drum brake system requires several essential components.

The brake booster works in conjunction with the master cylinder to amplify hydraulic fluid pressure generated by the brake pedal, enabling high torque power for effective braking This device provides the necessary force to activate the rod in the drum brake system, applying pressure to ensure efficient brake operation Designed to deliver consistent pressure regardless of the input force, the brake booster enhances overall braking performance.

Electronic components play a crucial role in automation, particularly in the automotive industry Key components include the Raspberry Pi-2 board, WiFi module, ultrasonic sensor, actuator, plunger, air compressor, LM3805, L293D, relay, resistors, and switches These electronic elements are integral to mechanical systems such as clutches, accelerators, and brakes Notably, a linear actuator converts circular motion into straight motion, enhancing functionality in various applications.

Conventional electric motors are commonly utilized in machinery tools and industrial applications These motors often drive hydraulic or pneumatic cylinders, which generate linear motion derived from the motor's rotation.

12 V input voltage and works on principle of moving the clutch.

The US-020 is an ultrasonic sensor model It is commonly used for the detection of distance or an obstacle It is an electronic component which is used in

The Arduino/Raspberry Pi system features a high-range sensor equipped with a transmitter, receiver, and control unit, capable of functioning in various lighting conditions, including direct sunlight and on black metal surfaces It includes four essential ports: Vcc, Gnd, TRIG, and ECHO The battery placement within the engine is illustrated in Fig 4, showcasing a specially designed unit that is durable and suitable for automotive applications, ensuring resilience in all weather conditions The rugged exterior is constructed from polypropylene, while the positive grid features rust-resistant materials and reinforced corners, and the negative grid provides an expansive ground phase.

The specification of the battery is given in Table1.

Fig 4 Battery in the engine

Battery brand Exide little champ Battery type EXLC35L lead acid Dimension 197(L) * 129(W) * 227(H)

The complete circuit design and implementation are illustrated in Fig 5, where connections are established according to the provided circuit diagram The actuator is linked to the clutch, while the plunger connects to the accelerator Additionally, the air compressor interfaces with the auto drum brake system The engine is initiated using a kick-start method, as programmed in the Raspberry Pi, and the UV sensor is activated to measure distance.

Based on the programming while the engine starts:

• The switch is pressed, and the ignition is started.

• First, the clutch is pressed and held for 0.5 s.

• On that time interval, the gear is made to change manually.

• After the time interval, the clutch is slowly released as how the human legs released by actuator.

• Then, the plunger is made to pull the accelerator, and the vehicle is moved at

20 kmph at an ideal speed.

• If the UV sensor detects 200–250 cm distance, the de-acceleration is done, whereas the plunger releases the accelerator by using relay.

• So that in this case, the vehicle is made to run at 10 kmph.

• After the distance is normal, the vehicle goes on to normal function.

• If the UV sensor suddenly detects at 150–200 cm distance, the braking is applied.

• The clutch is made to press in half mode, whereas the plunger is made to release the accelerator at same time by using relay.

• Then, the air compressor is made to be on by the relay board, and then, the air is given to drum brake system, and the brake is applied.

• After the normal distance at instant time, the air is made to be released manually,and then, the vehicle is made to move as per distance detected in sensor.

The engine starting results are illustrated in Fig 6, where the ECU, programmed on a Raspberry Pi, awaits sensor signals The nearest vehicle is detected at a distance of 213.17 cm During engine startup, the system recognizes the clutch press, gear change, and clutch release, which allows for acceleration and vehicle movement As the vehicle moves, the sensor identifies obstacles and calculates varying distances, as depicted in Fig 7, according to the testing scenario.

Fig 9 After brake pedal pressed

During low-speed engine operation, automatic deceleration activates, as illustrated in Fig 8 The vehicle's initial distance is 331.98 cm, which reduces to 220.55 cm due to low speed This decrease in distance and the activation of deceleration are prominently displayed to ensure driver awareness.

Thirkell and R Chen

The automotive industry is under growing pressure to minimize harmful emissions, prompting heightened research and development efforts for alternative power sources such as batteries and fuel cells that offer ultra-low emissions.

To explore the integration of fuel cell systems in automotive applications, it is essential to compare gaseous and liquid fed fuel cells Gaseous fuel cells, particularly the polymer electrolyte membrane fuel cell, are gaining popularity due to their high power densities and reliance on hydrogen In contrast, liquid fuel cells, like the emerging direct methanol fuel cell, are less common but offer promising potential for automotive use, as methanol storage resembles that of conventional fuels such as petrol and diesel.

Keywords Polymer electrolyte membrane fuel cell (PEMFC)ã Hydrogen ã Direct methanol fuel cell (DMFC)ã Methanol ãElectric vehicle

Peer-reviewed under responsibility of the scientific committee of the International Conference on Progress in Automotive Technologies, ICPAT—2019.

Loughborough University, Loughborough LE11 3TU, UK e-mail: A.Thirkell@lboro.ac.uk © Springer Nature Singapore Pte Ltd 2021

PEMFC Polymer electrolyte membrane fuel cell

The automotive industry faces mounting pressure to cut harmful emissions, especially carbon dioxide (CO2) To achieve lower emissions, innovative ultra-low emission powertrain designs are essential, prompting a heightened emphasis on the research and development of alternative power sources, primarily batteries and fuel cells.

Hybrid electric vehicles (HEVs) play a crucial role in reducing harmful emissions and promoting low-emission technologies Despite their benefits, HEVs rely on internal combustion engines as either the main or supplementary power source, which means they cannot completely eliminate harmful emissions.

The transition from hybrid electric vehicles (HEVs) to battery electric vehicles (BEVs) is a natural progression in the automotive industry While pure BEVs offer the significant benefit of zero emissions, they face challenges such as limited driving range and extended charging times In the UK, the average range of the top three BEVs—Nissan Leaf, BMW i3, and Renault ZOE—highlights these limitations.

≈160 miles This is around half of the expected range of most fossil fuel cars.

To address range anxiety, enhancing the energy storage density of electric vehicle systems is essential This can be achieved by exploring advanced high-energy-density battery technologies or by incorporating a secondary power source, such as fuel cells (FC), as a range extender Fuel cells offer a zero tailpipe emission solution, utilizing an exothermic electrochemical reaction that combines fuel with oxygen, producing primarily heat and water as by-products Various fuel cell technologies demonstrate potential for automotive applications, which will be analyzed in this paper.

The fuel cell (FC) stack is the essential component where the chemical redox reaction between fuel and oxidant occurs This solid-state device contains no moving parts and consists of multiple individual cells that are electrically connected in series or parallel configurations.

The typical architecture of a single-cell fuel cell (FC) allows for the customization of individual cells within a stack to meet specific customer requirements for current and voltage Additionally, multiple smaller stacks can be electrically connected to create distributed architectures In a fuel cell, fuel, either in gas or liquid form, is introduced at the anode, while the oxidant is supplied at the cathode The initial reaction takes place at the anode catalyst layer, where the fuel is decomposed, and the resulting mobile ions, typically H+, pass through the polymer membrane These ions then combine with the oxidant at the cathode catalyst layer to complete the reaction Fuel cells offer a significant advantage over traditional internal combustion engines (ICEs) due to their high efficiency, which is not constrained by the Carnot limit, although they do not achieve 100% efficiency The Nernst equation can be applied to account for the irreversible voltage losses related to activation, ohmic resistance, and mass transport.

E 0 HHV Thermodynamic reversible voltage based on the higher heating value of hydrogen (1.23 V) [15–18]

T Operating temperature (K) α Charge transfer coefficient (0.5) [15,16]

Fig 2 Example polarisation and power curves for a PEMFC, produced in-house

I Current density (A/cm 2 ) i n Internal and fuel crossover equivalent current density (0.002 A/cm 2 ) [17,18] i 0 Exchange current density (3.0×10 −6 A/cm 2 )

Ohmic resistance (0.245 cm 2 ) [15] m Mass transport loss empirical constant 1 (3.0×10 −5 V) [15] n Mass transport loss empirical constant 2 (7 cm 2 /A) [15]

The polarization and power curves illustrated in Fig 2 demonstrate the impact of irreversible voltage losses on fuel cell (FC) performance Notably, the power curve indicates a decline in performance following the peak power output, which aligns with the reduction in cell voltage caused by mass transport losses within the fuel cell system.

Promising fuel cell technologies for the automotive sector include the gaseous polymer electrolyte membrane fuel cell (PEMFC) and the liquid-fueled direct methanol fuel cell (DMFC) In contrast, other fuel cell types, like solid oxide and alkaline fuel cells, face significant challenges to their adoption, including high operating temperatures, prolonged start-up times, and low levels of technological readiness.

Polymer electrolyte membrane fuel cells (PEMFCs) are the leading and most advanced type of gaseous fuel cells The half reactions for a PEMFC, represented by equations (2a, 2b), illustrate that each mole of hydrogen (H2) reacts to produce energy, highlighting the efficiency and significance of this technology in energy conversion.

Cost ≈ 4000 $/kW [29] electrons are made available A summary of key details concerning PEMFCs is given in Table1.

PEMFCs offer significant advantages over other fuel cell types, including simple low-temperature start-up and a high power density However, it is crucial to use pure hydrogen in low-temperature PEMFCs, as any fuel impurities can cause irreversible damage to the catalyst layer.

Proton Exchange Membrane Fuel Cells (PEMFCs) can function effectively across a broad temperature range, with studies indicating that their current production capabilities improve as temperatures rise Utilizing higher operating temperatures in automotive applications could provide an efficient heat source for cabin conditioning.

Direct methanol fuel cells (DMFCs) utilize liquid methanol (CH3OH) as fuel without the need for pre-processing, making them a popular choice among direct liquid fuel cells due to the advantageous properties of methanol The half reactions of a DMFC indicate that each mole of methanol consumed generates six electrons, suggesting that a DMFC can operate with one-third the fuel required by a proton exchange membrane fuel cell (PEMFC) for the same current output.

DMFCs and PEMFCs operate at comparable temperatures, as highlighted in Table 2 However, the performance of current DMFC stacks is limited by slow reaction kinetics and the tendency for methanol crossover from the anode to the cathode.

Shankar, Geoffrey Eappen, Shubham Mittal, and Ramit Mehra

Random deployment of wireless sensor networks (WSNs) often results in coverage holes, posing significant challenges to achieving optimal coverage To address this issue, we compare tree-based coverage hole detection, Delaunay triangulation, and Voronoi algorithms based on their effectiveness in identifying these gaps Our proposed method aims to minimize the number of sensors required by focusing only on the areas that need inspection, utilizing image recognition techniques to analyze pixel occurrences of black and white colors in scanned images This approach allows for the identification of the necessary deployment zones for additional sensors Furthermore, we will evaluate the performance of existing tree-based and triangulation algorithms alongside particle swarm optimization (PSO) to enhance coverage hole detection in WSNs.

Keywords Holeã Healing ãTree-based coverage hole detectionã Delaunay triangulationãVoronoi algorithmã Pixel ãParticle swarm optimisation

In Wireless Sensor Networks (WSNs), sensor nodes are randomly distributed throughout the region of interest (ROI) to detect events and gather information Each sensor node operates within a fixed circular range, enabling effective data collection and monitoring.

This article addresses the challenges of hole coverage, detection, and healing in Wireless Sensor Networks (WSNs), specifically utilizing Voronoi, Delaunay, and tree-based methods The goal is to minimize the number of additional sensors needed to cover uncovered areas, ensuring efficient sensor network deployment while effectively addressing uncovered regions.

School of Electronics and Communication Engineering, VIT University, Vellore 632014, Tamil Nadu, India e-mail: geofz121@gmail.com © Springer Nature Singapore Pte Ltd 2021

To enhance sensor deployment, we utilize particle swarm optimization to identify optimal areas based on color differentiation linked to intensity levels This approach not only improves coverage but also minimizes the need for additional sensors.

Wireless sensor networks (WSNs) have become a significant area of research, particularly in the detection of coverage holes Senouci et al addressed the challenges of hole detection and recovery in sensor nodes, emphasizing the need for high node density while minimizing coverage costs Qiu and Shen introduced a Delaunay-based, coordinate-free mechanism that identifies coverage holes without requiring precise location data, though it lacks a comprehensive view of the holes Additionally, Bejerano proposed a greedy algorithm that activates inactive nodes to fill gaps, but this approach suffers from high computational complexity, leading to increased energy consumption.

Ma et al [6] proposed a geometry-based method for detecting holes in a post-deployment area, emphasizing the necessity of knowing the sensor's actual location In contrast, Zhang et al [7] focused on identifying holes along a coverage boundary using innovative geometric techniques, which involve localized Voronoi diagrams and polygons that depend on the positions of one-hop neighbors.

The main idea is to improve the way we deploy sensors in order to save energy, cost and improve throughput general flow.

In our study, we deploy random nodes across a canvas and visualize the results using MATLAB We define a "hole" as any uncovered area resulting from sensor deployment By plotting the sensing radius of each node, we aim to identify and minimize these holes, ultimately striving for complete coverage To achieve this, we merge overlapping sensing areas, which reduces the number of sensors needed, thereby conserving energy and lowering costs Employing a tree-based approach, we address the holes and compare our results with Delaunay and Voronoi-based algorithms The comparative performance of these algorithms is illustrated, as shown in Figures 1a and 1b.

Fig 1 a General Flow of the deployment of the sensor nodes b General Flow for the PSO based hole detection

Fig 2 Random deployment of nodes

Begin by connecting the nodes to form a series of triangles, known as Delaunay triangulation This method asserts that the three points of each triangle create a vertex when they intersect the circumference of a circle, referred to as the circumcircle of the triangle Notably, these triangles are structured so that the circumcircle does not encompass any other nodes within the network The accompanying figure illustrates this concept clearly, with Figure 2 depicting a random deployment of nodes.

Here, in Fig.4, the ‘+’ symbol signifies a node The Voronoi diagram is made from the Delaunay triangles.

To create a Voronoi diagram from Delaunay triangles, first, mark the mid-points of all triangle lines and draw long perpendicular lines from these points After marking the intersection points, connect them to form the Voronoi diagram, where each node is assigned its own area If a node can adequately cover its designated area with its sensing circle, it has fulfilled its task However, in most scenarios where this coverage is insufficient, additional sensors are required to optimize the coverage of any holes Figure 4 illustrates the individual regions for all nodes.

Fig 3 Delaunay triangles with respective circum circles

Fig 4 Voronoi—individual regions of all nodes [1]

The radius of the circular sensing disc is denoted byR s,and similarly, the radius of the empty circle isR e

The detection of uncovered regions of interest utilizes the concept of empty circles, specifically the circumcircles of Delaunay triangles By comparing the radii, R_e and R_s, for each uncovered region, we can identify areas where R_e exceeds R_s, indicating the presence of uncovered regions within the vacant circle Consequently, when the sensing radius surpasses R_s, the focus shifts from hole detection to the determination of holes.

3.4 Concept of IEC (Inscribed Empty Circle)

Empty circles do not guarantee total similarity with coverage holes, providing only a general concept As illustrated in Figure 5, the grey areas within the green empty circles indicate instances where R e exceeds R s.

Here, the proposed scheme is introduced as:

Fig 5 Hole detection through empty circles [1]

Inscribed empty circles (IECs) are used to estimate the sizes of coverage holes in a given area An IEC is defined as a circle that shares the same center as its corresponding empty circle The radius of the inscribed empty circle, denoted as R_ie, is determined by the difference between the radius of the empty circle (R_e) and the sensing radius (R_s), with R_e being larger than R_s.

In this illustration, the black circle represents an empty circle with a radius of Re, while the red circles denote identical sensing circles, each with a radius of Rs Additionally, the green circle signifies the IEC, which is defined by its specific radius.

=R e−R s[1] The centres of the sensing circles are outside the empty circle, as the empty circle is a circum circle of a Delaunay triangle (Fig.6).

1 If this length turns out to be more than 2R s, then the two behave to be in the same coverage hole (e.g.—[C1, C2) and (C2, C3) and (C3, C4)] [1].

2 Else, if it turns out to be less than 2R sand the holes are merged as one (e.g.—C4,

3 Else, the holes are said to be different holes (C1, C2, C3, C4, C5and C6)

To minimize the deployment of sensors while conserving energy and reducing costs, a new method is introduced that merges empty circles associated with the same coverage hole, following the IEC concept The merged circles are visually represented in the same color for clarity.

0020, and merging of isolated IECs are shown in Fig.7.

In Fig 8, the merging of certain empty circles results in a reduced number of red circles, effectively addressing the coverage holes illustrated in Fig 9.

Here, in Fig.10we do hole detection through IEC with tree-based method [6] A tree is formed by joining the centres of all the IECs [7] Here, the blue line segments

Fig 7 Merging of isolated IECs [1] join the centres of all the IECs, which forms a tree Hence, the blue lines together form a tree.

Figure11depicts the hole dissection—here, the green and blue lines indicate two different sub-trees [1,14] The proposal of dissection of a large coverage is done as [1].

Shankar, Geoffrey Eappen, and S Rajalakshmi

In recent years, communication systems have advanced significantly, largely due to innovative algorithms in wireless sensor networks This paper introduces three novel algorithms that enhance the traditional A-star algorithm to optimize routing between source and destination nodes The focus is on minimizing path length, which subsequently decreases execution time and resource consumption The proposed algorithms include diagonal A-star (DA*), which allows diagonal path searches; bidirectional A-star (BIDA*), enabling simultaneous traversal from both source and destination; and a combined diagonal-bidirectional approach that integrates the strengths of both methods Together, these algorithms offer a more efficient routing solution.

Keywords Routing A-star (A*)ãDiagonal A-star (DA*)ãBidirectional A-star (BIDA*)ãDiagonal-bidirectional A-star combined (DBIDA*)ãPath lengthã

Routing is a crucial element in wireless sensor networks, enabling the establishment of efficient connections through robust algorithms It involves determining the optimal path between source and destination nodes Although numerous routing algorithms exist to facilitate this process, there remains a need for more optimal solutions tailored to diverse environments and conditions To address this gap, three new robust routing algorithms have been developed.

School of Electronics Engineering, VIT University, Vellore 632014, Tamil Nadu, India e-mail: geofz121@gmail.com © Springer Nature Singapore Pte Ltd 2021

This paper introduces three algorithms: Diagonal, Bidirectional, and a combined Diagonal-Bidirectional approach, all aimed at optimizing the path between a source and a destination Section 2 outlines modifications made to an existing algorithm to enhance path optimization Section 3 details the proposed algorithm, while Section 4 presents a comparative analysis of the results from all three proposed algorithms against the traditional A-star algorithm, leading to a conclusive evaluation.

The A* algorithm is a popular pathfinding method utilized to determine the shortest route between a starting point and a destination It calculates the total cost using the formula f(n) = g(n) + h(n), where g(n) represents the actual cost of the path from the source to the destination, and h(n) indicates the heuristic cost from node n to the goal node.

The algorithm utilizes an open list to maintain a set of all possible nodes (visited nodes) and a closed list for nodes that pave the path A key drawback of this algorithm is its efficiency, prompting enhancements to the A* algorithm in the proposed concept The refined A* offers improved optimality through the introduction of three new concepts.

To reduce the number of nodes in the open list, a diagonal concept has been introduced, which examines all neighboring nodes rather than just the four adjacent ones This approach utilizes diagonal traversal to shorten the distance between the source and destination The flowchart for the A* algorithm is illustrated in Figure 1.

Fig 1 Flowchart for bidirectional A* search [3, 12–14]

The algorithm is defined as follows:

(1) First step is to place the source node in open list.

(2) If open list is empty, then return false and stop.

(3) Select the successor from the eight possible neighbouring nodes and place it in the open list.

To optimize the search process, transfer the node with the lowest f(n) value from the open list to the closed list If this node is identified as the goal node, the algorithm successfully concludes and terminates.

(5) If it is not the goal node, then expand all the successors of the node in close list and maintain them in the open list.

The flowchart in Figure 1 illustrates the diagonal A* search algorithm, which incorporates a bidirectional approach to enhance pathfinding efficiency In this method, node traversal occurs concurrently from both the source and destination points As a result, bidirectional A* proves to be more time-efficient than both diagonal A* and traditional A* algorithms.

(1) First step is to place the source node and the destination in open list.

If the node in the open list has a low value off(n), it should be removed and added to the closed list for both the source and destination traversal nodes When the source and destination traversals converge, the process is considered successful, and the operation concludes.

(4) If not, then expand all the successors of the node in close list and maintain them in the open list.

To enhance efficiency, the diagonal and bidirectional algorithms have been integrated to create a new algorithm that outperforms both of its predecessors This innovative approach is illustrated in the flowchart for the diagonal-bidirectional A-star algorithm.

Fig 2 Flowchart of diagonal-bidirectional A-star algorithm [3, 17, 18]

(1) First step is to place the source node and the destination in open list.

(3) Select the successor from the eight possible neighbouring nodes for both the source and destination traversal nodes and place it in the open list.

When the node in the open list has a low value off(n), it should be removed from the open list and added to the closed list for both the source and destination traversal nodes If the source and destination traversals converge, the process will return success and terminate.

(5) If not, then expand all the successors of the node in close list and maintain them in the open list.

Diagonal A* search expands its search capabilities by considering all eight neighboring nodes instead of just the traditional four, allowing it to navigate in all directions more effectively This approach enhances the algorithm's ability to identify the most efficient shortest path, which can then be added to the closed list for optimal route planning.

The operation of diagonal A* search was described and shown in Fig 3a–f,

In a 7×7 matrix, the source node S is located at (7, 4) and the destination node D is at (2, 2) Diagonal search operates similarly to A* search but differs by selecting successors from eight neighboring nodes instead of just four This approach enhances efficiency compared to A*, as it reduces the time required to determine the optimal path.

To reduce the time of path finding, bidirectional concept is deployed In bidirectional A*, traversing of nodes starts from both source and destination simultaneously [1,

Bidirectional A* search operates by simultaneously traversing from both the source node S at (7, 4) and the destination node D at (2, 2) within a 7 × 7 matrix, as illustrated in Fig 4a–d Unlike traditional A* search, which explores only one side, bidirectional search enhances efficiency by reducing the time required to identify the optimal path.

S D c.Choosing of successor nodes e Choosing next successor nodes b.Source traversing d Source traversing f Path from source to destination

(a) An example for Diagonal A* search

Fig 3 a An example for diagonal A* search b Source traversing c Choosing of successor nodes. d Source traversing e Choosing next successor nodes f Path from source to destination

S D b Source and Destination c Choosing of successor nodes both the sides d.Choosing of successor nodes both the sides and path is chosen

S D a An example for Bidirectional A* search

Fig 4 a An example for bidirectional A* search b Source and destination c Choosing of successor nodes both the sides d Choosing of successor nodes both the sides and path is chosen

The project discusses computer simulations illustrating various pathfinding algorithms, including the diagonal A* algorithm (Figure 5), the bidirectional A* algorithm (Figure 6), and the combined diagonal-bidirectional A* algorithm (Figure 7) In these figures, the source is represented in red, while the destination is marked in green, highlighting the paths from the source to the destination.

Fig 5 Path from source to destination by applying diagonal A* algorithm

Fig 6 Path from source to destination by applying bidirectional A* algorithm

Fig 7 Path from source to destination by applying diagonal-bidirectional A* combined algorithm

Muthukumar, A Ragul Aadhitya, N Rengarajan, K Sharan,

Air pollution is a critical global issue, and fuel cells represent a promising technology to mitigate this problem These electrochemical devices generate electricity through the reaction of hydrogen and oxygen gases, with proton exchange membrane (PEM) fuel cells being the most cost-effective option Operating at low temperatures between 50 °C and 80 °C, PEM fuel cells are eco-friendly as they emit no harmful gases The performance of these fuel cells is influenced by various factors, including the properties of materials used in components like the gas diffusion layer, membrane, and catalyst layer, as well as flow channel designs and water management The membrane, typically made of polytetrafluoroethylene, selectively allows protons to pass from the anode to the cathode while blocking electrons This study analyzes the performance of PEM fuel cells using two different membranes, Nafion 117 and Nafion 212, with a serpentine flow field configuration on both sides The designed PEM fuel cell, featuring an active area of 11.6 cm², demonstrates that the Nafion 212 membrane yields higher power output under optimal operating conditions.

Keywords EmissionãEco-friendlyã Membrane ã Nafion ã Power

Department of Mechanical Engineering, Nandha Engineering College, Erode 638052, India e-mail: muthupsgtech@gmail.com

Department of Electrical and Electronics Engineering, Nandha Engineering College, Erode

Department of Automobile Engineering, PSG College of Technology, Coimbatore 641004, India © Springer Nature Singapore Pte Ltd 2021

M-GDL Metal Gas Diffusion Layer

PEMFC Proton Exchange Membrane fuel cell

Global warming and ozone layer depletion are escalating due to emissions from vehicles and appliances Ongoing research aims to find alternative energy sources to mitigate air pollution, with fuel cells emerging as a promising renewable energy solution Unlike batteries, which store energy chemically, fuel cells can provide continuous power as long as they receive a supply of gases Among the various fuel cell types, Proton Exchange Membrane (PEM) fuel cells stand out for their high efficiency, low maintenance, long lifespan, compact size, and lower operating conditions compared to conventional internal combustion engines PEM fuel cells are commonly used in uninterrupted power supplies (UPS) for both residential and commercial applications, as well as in stationary power sources.

The performance of PEM fuel cells is affected by factors including water management, flow channel design, operating conditions, and the materials used in the catalyst layer and membrane Research indicates that serpentine flow channel designs optimize efficiency and power output Key components such as bipolar plates, catalyst layers, and gas diffusion layers are typically constructed from graphite, carbon paper, and platinum-carbon alloy Various types of Nafion membranes, including Nafion HP, Nafion 1110, Nafion 212, and Nafion 211, play a crucial role in the overall performance of the fuel cell.

117, etc In this paper, the performance of fuel cells with Nafion 212 and Nafion 117 membranes is analyzed in detail.

Proton exchange membrane fuel cells utilize a membrane composed of polytetrafluoroethylene (PTFE), a synthetic polymer known as an ionomer This membrane's primary role is to separate electrons from hydrogen gas, allowing only protons to pass through, which is the basis for its name The freed electrons travel through an external circuit to the cathode, where they react with oxygen gas to produce water and generate a small amount of heat The efficiency of this reaction is further enhanced by catalytic activity, contributing to the overall performance of the fuel cell.

Water movement across the membrane, whether from the anode to the cathode or vice versa, is influenced by the membrane's thickness, which affects proton conductivity and water cross flow The performance of a fuel cell is significantly impacted by the moisture content of the membrane; excessive water accumulation on the cathode side can cause flooding and reduce efficiency, while complete dehydration can damage the membrane and the membrane electrode assembly (MEA) Given the high cost of the membrane and catalyst, enhancing their durability is crucial Therefore, maintaining an optimal water level within the membrane is essential for effective fuel cell operation.

2 Influence of Design and Operating Parameters on the Performance of Fuel Cell

Kahveci and Taymaz developed a PEM fuel cell model featuring a single serpentine flow channel using computational fluid dynamics Their three-dimensional polymer electrolyte membrane has an active area of 25 cm² and was analyzed within a temperature range of 333–335 K, pressure levels of 1–3 atm, a GDL thickness of 0.3 mm, and relative humidity levels from 10% to 100% The experiments revealed that the performance of the PEM fuel cell improved with an optimal increase in temperature, although it is crucial to ensure that the temperature does not exceed certain limits.

Research by Ghanbarian et al explored the design of a parallel serpentine flow field with an active area of 5×5 cm², revealing that performance improves with increased porosity of the gas diffusion layer (GDL) The study examined various parameters, including the number of serpentine turns, parallel channels, ribs between adjacent channels, and channel dimensions To optimize the design, six filtering constraints were applied to reduce the number of viable configurations for effective flow fields.

The result produced the best serpentine-type flow field configuration for the given operating condition with geometrical specification as (L,n,s,w,d,h)=(249, 5, 4,

Karthikeyan et al developed a 3D model of PEM fuel cells to optimize ten parameters using the Taguchi method with an L27 orthogonal array The optimized parameters included back pressure, cell temperature, GDL porosity, channel dimensions, porous electrode thickness, GDL thickness, and inlet velocities Muthukumar et al analyzed PEM fuel cell performance with a fixed channel length of 20 mm and varying landing to channel widths, finding that the 0.5 mm × 0.5 mm design achieved the highest power density of 0.4473 W/cm² and current density of 1.1183 A/cm², outperforming other designs despite their larger active areas Additionally, the effects of pressure and temperature on taper and serpentine channel designs were investigated.

Ashrafi et al [7] investigated a modified Z-type flow field with a 26.52 cm² active area to enhance the uniformity of two-phase flow in parallel systems Their experiments revealed that while power and efficiency remained stable at high cathode stoichiometric ratios, the overall output was low A 3D numerical model was then employed to modify the flow field, demonstrating that the parasitic power for the air supply system was reduced compared to a simple flow field, resulting in improved overall efficiency Similarly, Wen et al [8] numerically analyzed an intersectant flow field design with a 15 mm x 15 mm active area, incorporating a 1 mm diffusion layer, a 1 mm catalyst layer, and a 0.1 mm membrane thickness Their study utilized current density, oxygen distribution, polarization curves, and water mass distribution to optimize the flow field, using a single serpentine flow field as a reference The optimal channel porosity and width were determined to be 0.5 mm and 0.3 mm, respectively, with experimental results indicating ideal hydrogen and air flow rates of 300 ml/min and 500 ml/min at an operating temperature of 80 °C.

Heidary et al [9] explored the impact of varying pressure, temperature, and water saturation on the cathode catalyst layer (CL) of PEM fuel cells using a macro-homogenous model Their findings indicated that saturation levels significantly affected CL performance, with improvements of 19% and 30% at 0.11 V, and 9% at 0.05 V, as temperature increased from 40 to 90 °C, saturation decreased from 75% to 25%, and operating pressure rose from 3 to 7 atm Meanwhile, Yang et al [10] examined the performance of dead-end anode (DEA) configurations in PEM fuel cells, comparing three anode flow field designs—parallel, serpentine, and interdigitated—with and without anode exit reservoirs across various operating modes.

The study found that the serpentine flow field with diethylamine (DEA) demonstrated stable operation when paired with an anode exit reservoir and pressure swing operation In contrast, the parallel flow field was deemed unsuitable for use with DEA in proton exchange membrane (PEM) fuel cells.

Zehtabiyan-Rezaie et al investigated the performance of PEM fuel cells using converging and diverging flow channels, revealing a 16% increase in electrical power output with 0.3° inclined channels compared to conventional parallel flow channels Similarly, Wang et al explored various cathode flow channel geometries, including semicircle, trapezoid, and triangle shapes, and found that the triangular channel outperformed the others in terms of performance and water removal, with all channels having specific dimensions for height and layer thicknesses.

3 Influence of Materials of Components on the Performance of Fuel Cell

Palaniswamy et al conducted a study on fuel cell performance using active areas of 70 and 25 cm² with various channel designs, including serpentine, zigzag, and uniform pin types Their findings revealed that carbon inserts made from Vulcan carbon, with 80–90% porosity, enhanced power density and current density by 11.5% and 7%, respectively, while also improving water removal due to their high porosity, electrical conductivity, and water absorption capabilities Additionally, Hu et al explored the use of Cr2N-coated bipolar plates in PEM fuel cells through pack cementation, achieving a Cr2N coating by heating a powder mixture at 1100 °C for 4 hours, resulting in an outer Cr2N layer and a Cr-rich interdiffusion zone with thicknesses of 18 µm and 13 µm, respectively.

H2SO4solutions at 60 °C confirmed the pinhole-free feature and corrosion resistance of Cr 2 N-coated plates.

Salahuddin et al explored the use of polyacrylonitrile (PAN) nanofibers in gas diffusion layers (GDL) for PEM fuel cells, finding that their innovative GDL outperformed traditional designs by effectively managing water flooding through enhanced hydrophilic properties Havaej et al examined the impact of varying catalyst loading distributions in both longitudinal and lateral directions, concluding that a non-uniform distribution significantly improved cell performance, particularly when maintaining a platinum ratio of 1.857 between gas channel inlets and outlets Wu et al focused on optimizing the arrangement of protrusive GDLs in PEM fuel cells, utilizing the Taguchi design of experiments to identify the most effective pattern for enhancing performance.

Recent studies have highlighted significant advancements in the performance of Proton Exchange Membrane (PEM) fuel cells Alshorman's research demonstrated that using a biological cellular membrane with a thickness of 0.0006 cm and a current density of 0.4–1.2 A/cm² increased the output power by 33% compared to conventional membranes, producing 17% more power at the same hydrogen pressure Yurtcan and Das explored a carbon black hybrid catalyst synthesized with reduced graphene oxide, finding that a 70:30 rGO to CB ratio optimized PEM fuel cell performance Shiro Tanaka and Arnaud G Malan's numerical analysis revealed that a perforated metal gas diffusion layer (M-GDL) improved fuel cell performance by 9.4% due to its effective frame width and pore size Additionally, ệztỹrk and Yurtcan investigated porous N-doped carbon nanotubes combined with polypyrrole, showing that 12-hour activated N-CNTs produced a higher surface area and better catalyst support than those activated for 18 hours Lin et al examined high-temperature PEM fuel cells using protic ionic liquid graphene oxide hybrid membranes, which exhibited excellent mechanical properties and thermal stability Overall, these studies underscore the impact of various designs, operating conditions, and materials on the performance of PEM fuel cells, with a particular focus on the effects of different membranes.

Raja, C D Naiju, M Senthil Kumar, and N Navin Kumar

Driver comfort and positioning are critical for enhancing race car performance This study proposes design improvements for a comfortable racing seat, resulting in a prototype aligned with cockpit specifications Impressions of four drivers' vertebrae and thighs were captured using expandable urethane foam and converted into point cloud data through 3D scanning The refined data led to a single optimized seat design that accommodates all drivers comfortably A comparative analysis of lap times using data acquisition (DAQ) validated the new seat design, revealing that the car with the existing seat experienced a more significant increase in lap times compared to the car equipped with the new design.

The interaction between humans and machines plays a crucial role in product design, particularly in the automotive industry Ensuring driver comfort is essential for effortless vehicle handling, allowing drivers to maintain focus and alertness, especially on racetracks By incorporating driver-specific comfort seats, manufacturers can significantly enhance driver performance and overall experience.

School of Mechanical Engineering, VIT University, Vellore 632014, India e-mail: cdnaiju@vit.ac.in

127 driver safety and, at the same time, provides enough room within the cockpit to maneuver the car with utmost efficiency.

A primary design objective in race car cockpits is to ensure that all drivers are comfortably accommodated Current design strategies often fall short, as they typically require driver-specific seat designs rather than a universal solution The industry seeks a single seat that can fit all drivers without the need for inserts or modifications Many existing approaches rely on anthropometric data, aiming for a "design to fit everyone" philosophy, but this does not guarantee individual comfort For instance, designing a seat based on the dimensions of the 95th percentile male and 5th percentile female can result in excessive space, leading to inefficient driver positioning and restricted movement This extra space can cause discomfort and awkward postures, which should be avoided to enhance overall driver performance and safety.

The importance of comfort seat design is growing, necessitating statistical analysis to explore the correlations between measurable and subjective comfort Accurate driving posture measurement is essential for enhancing seat comfort, with body pressure distribution data analyzed for contact area, average pressure, and body part pressure ratios Challenges arise in reverse engineering due to the varying effectiveness of point cloud data from different scanning devices Research has focused on driving posture evaluation, employing 3D laser scanning to reconstruct driver postures in real vehicles Additionally, photogrammetric techniques analyze images or video frames from various angles to create dense surface models or point clouds However, while seat inserts can be tailored to a driver's dimensions, they often provide limited support and are impractical to change for each driver during dynamic events Consequently, a new design process is needed to develop a single seat that accommodates the diverse body structures of different drivers.

A CAD model of a seat is created using anthropometric data, focusing on driver heights ranging from 155 cm to 195 cm However, these seats may not provide optimal comfort as they are not tailored to individual drivers To capture the shape of the largest driver, expanding foam is utilized, which is then machined for a smooth finish before being reinforced with glass or carbon fiber for manufacturing This composite construction adds weight to the seat, ultimately compromising driver comfort since the design is based solely on the dimensions of the tallest driver.

Expanding foam is utilized to create personalized molds from drivers' back impressions for individual seating; however, this time-consuming and costly process often fails to provide a secure seating position The foam inserts, tailored for each driver, need to be replaced for different individuals, complicating driver changes during dynamic events A prototype was developed to capture essential cockpit dimensions, focusing on an optimal hip point position based on data from a diverse group of race drivers After constructing the apparatus, adjustments were made to achieve a balance of comfort and visibility without compromising the car's dynamic performance This final setup not only ensured a comfortable seating system but also played a crucial role in the car's packaging parameters and chassis design.

The chassis was designed with careful consideration of the steering wheel position and other control elements, such as pedals and safety belts To capture the vertebral and thigh impressions of four drivers, a large polybag filled with two-part urethane foam was placed in the cockpit, allowing each driver to sit on it individually These impressions were then 3D scanned using photometry, and the resulting point cloud data was refined to create tessellated surfaces These surfaces served as a reference for developing a CAD model of a single seat, optimized to accommodate all four drivers effectively.

3 Seating Position Mapping and Manufacturing

A reclined driver position is essential for lowering the car's center of gravity, as drivers typically account for about 20% of the vehicle's total weight This adjustment enhances lateral acceleration, especially with appropriate suspension modifications Additionally, the reclined position offers aerodynamic benefits by reducing frontal surface area, which significantly decreases drag and improves rollover stability during cornering.

An apparatus was developed to measure critical cockpit dimensions, including the heights of the main and front hoops, seatback and thigh angles, steering location, dash height, cockpit width at various points, and pedal positioning The back and thigh angles significantly influence seat and cockpit design Drivers tested the apparatus and provided feedback, leading to a consensus on a seat design with a 45° back angle and a 55° thigh angle These specifications guided the seat's design and manufacturing process Following the chassis construction, impression molds were created, and a jig was designed to maintain the required seating angle for the drivers during mold creation.

The jig features a three-part structure with an adjustable seating area, fixed back, and thigh support tailored to specific angles To capture the vertebral and thigh impressions of four drivers, four polybags filled with expandable two-part urethane foam were utilized Each polybag contained one liter of polyurethane foam, which was thoroughly mixed before use The polybag was positioned on the jig, and the driver sat on it, allowing the foam to expand and form an impression around their body This procedure was repeated for all four drivers to create their respective impressions Finally, the mold was cleaned by removing any unwanted materials.

Fig 1 Curved plates with single impact with meshed model

Fig 2 Impression mold is formed when hardened

Fig 3 Final mold obtained after cleaning

4 3D Scanning and Point Cloud Data Processing

The molds were scanned using photometry, a non-contact passive 3D scanning technique that captures multiple images under varying lighting conditions By utilizing different luminosity levels, the system enables the computer to calculate depth at each pixel by estimating the surface normals of the object This method relies on detecting visible light, which serves as readily available ambient radiation for accurate analysis.

Photometry was chosen for its simplicity in the scanning process, utilizing inexpensive passive imaging with standard digital cameras To minimize reflections, polybags were painted black, and scanning was conducted on a Lambertian surface to ensure isotropic surface luminance for accurate results The impression molds were scanned at FARO’s facility in Chennai, with the resulting point cloud data processed using Geomagic Wrap 3D Imaging Software.

The driver position was consistent across all four drivers, with uniform back and thigh angles, allowing for effective merging of data based solely on driver body contours Using specialized software, the point cloud data files from all molds were aligned and merged, highlighting areas with high point population Noise and low point population areas were filtered out from the merged data Subsequently, the refined data was transformed into a surface through tessellation, and this surface file was exported in IGES format for the final seat design.

Fig 4 Merged point cloud data of all four impression molds

Fig 5 Surface formed over the merged point cloud data

The scanned image underwent further processing in SolidWorks, serving as a reference for the CAD model of the final seat, illustrated in Fig.6 To develop intersection curves, perpendicular planes were established along the seat contour at various points The placement and quantity of these planes were determined by the ergonomic significance of key areas, including shoulder support, lower back, hip support, thigh support, and arm support Consequently, the resulting impression mold was asymmetric.

The impression mold foam exhibited uneven contours, with notable differences between the left and right thigh and shoulder areas To address these irregularities, a refined contour was applied to both sides of the seat, smoothing the scanned mold's surface This final grid of curves facilitated the creation of a loft surface, which was integrated into the car's assembly to enhance design and packaging Adjustments were made to ensure proper clearance with the firewall and steering column, while also accommodating necessary elbow room for shifting Mounting points for the seat were extended as flanges to rest on chassis members, achieving a complete cockpit closeout and improving aesthetics Additionally, provisions for a six-point driver harness system were incorporated into the seat, culminating in a well-designed CAD model that was effectively packaged within the car.

Ramkumar, George Ranjit, Vijayabaskaran Sarath, V Vikraman,

Bagavathy Suresh, Namani Prasad Babu, and Malekar Amit

The lubrication system is crucial for engine durability, and careful design and validation are essential to prevent premature component failure, which can harm the manufacturer's brand image This article details the design process for a four-cylinder diesel engine's lubrication system, including concept design, optimization, and validation Oil pressure distribution is simulated, and design iterations are performed to adjust oil pressure levels across various galleries The findings on oil pressure at different galleries are systematically documented to enhance the lubrication system design, providing valuable insights into the optimization process.

Keywords Lubrication system designãOil pressure distributionãOil gallery pressureãEngine durability

DR Drive ratio lpm Litres per minute

J Ramkumar ( B ) ã G Ranjit ã V Sarath ã V Vikraman ã B Suresh ã N P Babu ã M Amit Mahindra Research Valley, Mahindra & Mahindra, Chennai, India e-mail: jayaraman.ramkumar@mahindra.com © Springer Nature Singapore Pte Ltd 2021

Ensuring engine durability is a top priority for designers, as functional requirements are essential and often taken for granted Designers invest significant effort to ensure engines meet their claimed warranty life and end-of-life standards With increasingly knowledgeable and sensitive customers, manufacturers face the risk of lawsuits if engines fail within the warranty period, leading to substantial financial losses from part replacements and legal fees Consequently, engine designers proactively address durability concerns during the design, simulation, and validation phases to mitigate potential issues.

Proper lubrication is essential for engine components that experience relative motion, as inadequate lubrication can lead to excessive wear and tear While it is impossible to completely eliminate wear and tear in moving parts, effective lubrication can significantly mitigate these effects Designers focus on ensuring that engine parts are lubricated correctly to achieve controlled wear throughout the engine's lifespan, particularly during validation trials.

Validation trials are designed to simulate the engine's lifespan in real-world conditions, focusing on worst-case scenarios that customers may encounter During these trials, engine components undergo significant wear, which must remain within the designer's specified controlled wear limits After completion, the engine is disassembled to measure the wear of individual parts, ensuring they fall within acceptable limits If the wear values are satisfactory, this correlates to the overall qualification of the engine's longevity for the customer.

A well-designed lubrication system is crucial for managing controlled wear in diesel engines, as uncontrolled wear can lead to premature engine failure This system is essential for maintaining wear and tear within acceptable limits, highlighting the need for thorough design, simulations, and validations The authors of this study focus on optimizing lubrication system design, emphasizing its significant impact on engine life, friction, and overall performance Additionally, various initiatives have been undertaken to reduce fuel consumption and CO2 emissions, with research underscoring the critical role of oil temperature in controlling both wear and engine friction.

Previous studies have conducted extensive simulation and validation efforts, demonstrating significant advancements in predictive simulations However, optimizing simulation inputs to align simulated values with validated results remains a challenging task The literature emphasizes the critical importance of maintaining oil pressure, as thorough simulations in this area can significantly reduce time-consuming processes.

Table 1 Engine specifications and boundary conditions

The current study emphasizes the critical validation of oil pump drive designs through internal crankshaft mechanisms, addressing the common discrepancies between simulated and validated outcomes It highlights the necessity for comprehensive validation before finalizing designs, focusing particularly on achieving optimal oil pressure across all operating conditions Previous research has demonstrated the significance of optimizing pressure buildup and downsizing pumps, while also noting the benefits of reducing pressure drops across filters Overall, this work underscores the importance of oil retention in minimizing friction, thereby enhancing fuel economy, and provides a detailed exploration of lubrication design optimization.

A comprehensive study involving simulation and experimental analysis was conducted on a 1.5 L turbocharged diesel engine with four cylinders Initially, the lubrication system's layout was conceptually designed and simulated to evaluate oil pressure distribution at key points within the engine's oil galleries Following the simulations, experimental work was performed to validate the simulated findings and refine the design further The engine specifications are detailed in Table 1.

The lubrication system comprises essential components, including the oil sump, oil pump, oil filter, piston cooling jet, oil galleries, and throttle plugs The initial concept design for the lubrication system layout is developed by benchmarking against other engines and leveraging prior experience Specifications for the lubrication system utilized in the concept design are detailed in Table 2.

The oil pump, illustrated in Figure 1, is powered by the crankshaft via a chain and sprocket drive mechanism This setup allows the crankshaft to effectively transfer power to the oil pump Additionally, Figure 2 presents the lubrication oil circuit that services the entire engine, ensuring optimal performance and efficiency.

Table 2 Lubrication system specifications Description Specification

Oil pump type G-rotor type

Oil pump displacement 22.7 cm 3 /revolution Oil pressure limit (max) 3.95 bar (Gauge)

Oil pump drive method Chain and sprocket drive Oil pump drive ratio 1:0.76

Fig 1 Oil pump drive system layout oil passage lines/oil galleries of the engine are shown in detail highlighting the key components of lubrication system.

The oil circuit of the cylinder head, illustrated in Figure 3, features two extended oil galleries designed to lubricate both the intake and exhaust camshafts Additionally, lubrication lines reach the rear of the cylinder head, where the vacuum and fuel injection pumps are located, ensuring their proper lubrication The oil pressure and flow within these lubrication lines are regulated by a throttle plug situated at the entrance of the cylinder head oil gallery.

The throttle plug in an oil lubrication system intentionally reduces oil pressure and flow, limiting the amount of oil reaching the cylinder head oil gallery This design effectively decreases oil consumption for components like the hydraulic lash adjuster (HLA), camshaft, vacuum pump, and fuel pump, which do not necessitate high oil pressure for adequate lubrication.

Fig 2 Lubrication system layout for entire engine

The lubrication system layout for the cylinder head allows for a reduction in oil pump size by decreasing the flow to the oil galleries This change can significantly lower friction and costs associated with a smaller oil pump Additionally, using a smaller oil pump enhances packaging efficiency and contributes to a reduction in overall engine weight.

Recent research emphasizes the lubrication of cylinder head oil galleries, specifically the HLA oil galleries The authors detail the design and validation processes involved in determining the optimal throttle plug oil hole diameter and reducing the oil pump size, among other design optimization efforts.

The initial phase involves concept design informed by benchmarks and prior experiences Once the concept design is finalized, simulations are conducted using the commercially available CFD software "FlowMASTER." The simulation incorporates various input data, including gallery dimensions, volume, and bearing clearances As a 1D simulation tool, it simplifies data input to basic parameters like length and diameter for volume calculations Additionally, parameters such as oil temperature and oil characteristics, including viscosity and density, are entered into the software The first level of design evaluation is based on the results generated from these simulations.

Ravi, Jim Alexander, and E Porpatham

This study investigates the impact of turbocharger wastegate actuators on the performance and emissions of a twin-cylinder spark-ignited engine powered by LPG By operating the engine at wide-open throttle and varying speeds from 1000 to 3400 rpm, the research compares various performance and emission metrics between conventional and electronic wastegate systems Key parameters such as manifold absolute pressure, knock, and exhaust resistance were analyzed, with the electronic wastegate being calibrated to optimize performance based on engine demands Results demonstrated significant enhancements in brake thermal efficiency and a reduction in unburnt hydrocarbon emissions when using the turbocharger with an electronic wastegate.

Keywords TurbochargerãWastegate actuatorãLPG injectionãPerformance and emission

Peer-review under responsibility of the scientific committee of the International Conference on Progress in Automotive Technologies, ICPAT – 2019.

Automotive Research Center, School of Mechanical Engineering, VIT University,

The ongoing reliance on conventional engine technologies has spurred the development of new products focused on enhancing engine performance while effectively reducing emissions Downsizing techniques have emerged as a preferred method for optimizing spark ignition (SI) engines Among these innovations, turbocharging stands out as a modern approach that increases thermal efficiency and lowers emissions by introducing excess air, a benefit not typically seen in naturally aspirated engines.

The recent adoption of alternative fuels has significantly improved energy resource balance and enhanced automotive engine efficiency Liquefied petroleum gas (LPG) is a notable alternative fuel for spark-ignition (SI) engines, offering a low carbon content and a higher octane rating that reduces engine knock while minimizing emissions due to its favorable hydrogen-to-carbon ratio LPG also contributes to increased thermal efficiency and is compatible with higher compression ratios and optimized spark timing, making it suitable for multicylinder SI engines equipped with turbochargers Current turbocharger technologies, which utilize pneumatic actuators like vacuum or boost-type wastegate systems, face limitations in performance related to air flow rates and intake geometry.

Research indicates that changes in intake plenum geometry significantly impact engine performance and response times during transient operations Additionally, studies have focused on enhancing vehicle performance and drivability by controlling the actuator on the turbocharger turbine Implementing an adaptable wastegate actuator effectively reduces pumping losses during load variations and lowers fuel consumption.

Table 1 Properties of LPG fuel [5] Properties LPG

Butane C 4 H 10 —70% Lower heating value (MJ/kg) 45.7

Flame velocity (cm/s) 38.25Research octane number 103–105

To mitigate turbo-lag effects, implementing electronic wastegate control can provide precise management during engine start-up under low-pressure conditions.

The conventional method of turbocharging faces limitations at medium speed ranges due to knock effects that compromise wastegate actuation and result in power loss To address this, model-based approaches integrated with the engine control module (ECM) have been developed, utilizing sensors and actuators for real-time wastegate regulation Tests have shown that employing proportional integral derivative control can optimize manifold absolute pressure (MAP) at peak torque around 7200 rpm, where knocking intensities occur Studies indicate that closed-loop turbocharger control significantly enhances engine performance compared to traditional wastegate systems This research upgraded the existing boost type wastegate system to an electromechanical actuator based on a calibrated map, with experimental comparisons conducted among naturally aspirated, boost type, and electromechanically controlled turbocharger systems at full throttle.

The TATA Ace features a twin-cylinder, 704cc SI engine powered by compressed natural gas (CNG) and utilizes a port fuel injection system with liquid-cooled cylinders Operating under naturally aspirated conditions, it achieves a peak torque of 49 Nm at 2200 rpm and a maximum power output of 15.5 kW at 3400 rpm The engine's performance and emissions were evaluated with a KP35 turbocharger, with LPG fuel supplied at an operating line pressure of 2 bar to a common rail near the port region Air flow was measured using a Dresser air flow meter, while fuel flow rates were calculated based on the equivalence ratio and the stoichiometric air-fuel ratio of 15.3:1 for LPG An engine control module with a closed-loop feedback system monitored key functions such as throttle response and spark timing, allowing for flexible calibration across various performance maps The exhaust system included a turbocharger and intercooler to ensure stable combustion, and full throttle performance tests were conducted at speeds from 1000 to 3400 rpm under both naturally aspirated and turbocharged conditions.

Fig 1 Layout of the experimental setup

Fig 2 Intake boost and wastegate position with engine speed

The engine was tested with variable speed control using a Dynalec eddy current dynamometer, while emissions of hydrocarbons, nitric oxide, and carbon monoxide were measured with a Horiba five gas analyzer Initial baseline readings were taken under naturally aspirated conditions, followed by tests incorporating turbocharging with both conventional and electronic wastegates.

At full throttle conditions, key engine performance and emission parameters were evaluated, including brake power, brake torque, brake thermal efficiency, brake specific fuel consumption, exhaust gas temperature, and emissions of hydrocarbons, nitric oxide, and carbon monoxide.

The comparison of brake power between naturally aspirated and turbocharged engines reveals that the electronic wastegate significantly enhances performance, achieving a notable output of 14.3 kW at 3400 rpm This improvement is evident across all speed ranges, demonstrating superior efficiency over traditional turbocharging methods The electronic wastegate maintains consistent performance, as indicated by the calibrated table values.

Fig 3 Variations of brake power with engine speed

As engine speeds increase, conventional actuation systems encounter knocking at 2800 rpm, particularly in mid-range operations This knocking results from pumping losses that diminish enthalpy transfer to the turbine, causing insufficient pressure in the intake manifold and ultimately preventing wastegate actuation.

The output torque serves as a key indicator of load capacity, as illustrated in Fig 4 Traditional wastegate control features increased spring tension, which holds the valve in place and inadvertently creates exhaust back pressure, leading to a reduction in power and torque When the turbine's workload is exceeded, it can trigger knock formation at around 2800 rpm, primarily due to an initial delay and diminished compressor efficiency, resulting in insufficient intake manifold pressure necessary for proper actuation.

The electronic wastegate achieves peak torque of 47.5 Nm at 2200 rpm and maintains stability at higher speeds, demonstrating precise torque response through effective communication between the ECM, MAP sensor, and motor actuator.

Fig 4 Variations of brake torque with engine speed

Fig 5 Variations of brake thermal efficiency with engine speed

The brake thermal efficiency, which measures the conversion of fuel energy into work output, reached a maximum of 28.3% at 2200 rpm with the use of an electronically controlled turbocharger Excess air in the fuel-air mixture reduces the compression work needed to elevate the fuel temperature Additionally, the implementation of an air-cooled intercooler significantly lowers the overall charge temperature of the incoming compressed air, further enhancing brake thermal efficiency compared to naturally aspirated engines and conventional turbocharging systems.

Figure 6 illustrates the comparison of fuel consumption between naturally aspirated and turbocharged engines In lower and medium speed ranges, the increased engine vacuum results in throttling loss, which consequently leads to higher fuel consumption.

Whereas the turbocharger provided with the electronic wastegate system accurately monitors the MAP values and correspondingly determines the position of

Fig 6 Variations of brake specific fuel consumption with engine speed the wastegate that minimizes exhaust resistance and operating at regions of higher vacuum.

Bhaskar, Krishna Rawat, Muhammed Minhaj, M Senthil Kumar,

Tiêu đề	Advances in Automotive Technologies Select Proceedings of ICPAT 2019
Tác giả	M. Razi Nalim, R. Vasudevan, Sameer Rahatekar
Trường học	Purdue School of Engineering & Technology
Chuyên ngành	Mechanical Engineering
Thể loại	proceedings
Năm xuất bản	2021
Thành phố	Indianapolis

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Số trang	246
Dung lượng	12,51 MB