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The ever-tightening regulation norms across the world emphasize the magnitude of the air pollution problem. The decision to leapfrog from BS4 to BS6 – with further reduction in emission limits -showed India’s commitment to clean up its atmosphere. The overall cycle emissions were reduced significantly to meet BS6 targets [1]. However, the introduction of RDE norms in BS6.2 [1] demanded further reduction in emissions under real time operating conditions – start-stop, hard acceleration, idling, cold start – which was possible only through strategies that demanded a cost effective yet robust solutions. The first few seconds of the engine operation after start contribute significantly to the cycle gaseous emissions. This is because the thermal inertia of the catalytic converter restricts the rate at which temperature of the catalyst increases and achieves the desired “light-off” temperature.

Adaption of EV powertrains in existing vehicle architecture has created many unique challenges in meeting performance, reliability, safety, ease of manufacturing & serviceability at optimum cost. Mounting of large size battery packs in existing vehicle architecture is one of them. Specific energy & the energy density of Lithium ion batteries are very lower compared to Diesel & Petrol, which requires high volume & weight for equivalent energy storage. For movement of many passengers and to ensure sufficient range EV buses typically needs large amount of energy and for storage of same bigger size battery packs are required. These large size batteries directly affect vehicle architecture, seating layout, ease of assembly & serviceability. Moreover the heavy mass of batteries directly influences vehicle dynamics & performance characteristics such as vehicle handling, roll & NVH. The most important consideration in design of EV vehicles in general and buses in specific is safety.

Fuel cell electric vehicles generally have two power sources – the fuel cell power system and a high voltage battery pack - to power the vehicle operations. The fuel cell power system is the main source of power for the vehicle and its operations are supported by the battery pack. The battery pack helps to tackle the dynamic power demands from the vehicle such as during acceleration, to which the response of the fuel cell might be slower. The battery is also used to recover the energy from regeneration during braking and can also be used to extend the range of the vehicle in case the storage tanks runs out of hydrogen. In order to maximize the fuel efficiency of the fuel cell power system it is critical that these two power sources are used in conjunction with each other in an optimal manner.

Fuel cell electric vehicles (FCEVs) and battery electric vehicles are being touted worldwide by the automotive industry and policy makers as the answer to decarbonizing the transportation sector. FCEVs are especially suited for commercial vehicle applications as they offer very short re-fueling times that is comparable to conventional internal combustion engine vehicles. While this is entirely possible there are host of challenges that include safety, that need to be addressed to make short refilling times possible for commercial vehicles where the hydrogen storage requirement is higher (25 kg or more). This is due to the rise in temperature of the hydrogen in the cylinder due to compression and the negative Joule-Thompson coefficient. The SAE J2601 standard limits the safe temperature limit of hydrogen gas in the cylinder to 85 °C during filling.

This paper addresses challenges in current Fuel Cell Stack Buses and presents a novel Fuel Cell Electric Vehicle Bus (FCEV-Bus) powertrain that combines fuel cells, ultra-capacitors, and batteries to enhance performance and reliability. Existing Fuel Cell Stack Buses struggle with responsiveness, power fluctuations, and cost-efficiency. The FCEV-Bus powertrain uses a Fuel Cell stack as the primary power source, ultra-capacitors for quick power response, and batteries for addressing power variations. Batteries also save costs in certain cases. This combination optimizes power management, improves system efficiency, and extends the FCEV-Bus's operational life. In conclusion, this paper offers an innovative solution to overcome traditional fuel cell system limitations, making FCEV-Buses more efficient and reliable for potential wider adoption.

Computed Tomography (CT) has become a potent instrument for non-invasive assessment of battery cell integrity, providing detailed insights into their internal structure. The present study explores the capabilities and advantages of employing CT for cell characterization through a systematic evaluation from various parameters. The evaluation results will be based on real-world experiments conducted on a standard battery cell, assessing the CT system’s ability to provide precise internal measurements, detect defects, and ensure the overall integrity of the cell. We outline a comprehensive framework that includes criteria such as system specifications, image quality, software capabilities, maintenance, service, and cost-effectiveness.

This paper aims at analysing the effect of regeneration braking on the amount of energy harnessed during vehicle braking, coasting and its effect on the drive train components like gear, crown wheel pinion, spider gear & bearing etc. Regenerative braking systems (RBS) is an effective method of recovering the kinetic energy of the vehicle during braking condition and using this to recharge the batteries. In Battery Electric Vehicles (BEV), this harnessed energy is used for controlled charging of the high voltage batteries which will help in increasing the vehicle range eventually. Depending on the type of the powertrain architecture, components between motor output to the wheels will vary, i.e., in an e-axle, motor is coupled with a gear box which will be connected with differential and the wheels. Whereas in case of a central drive architecture, motor is coupled with gearbox which is connected with a propeller shaft and then the differential and to the wheels.

Since last decade automotive Industry is witnessing transition from ICE to EV due to stringent environmental laws by government bodies and technological breakthrough. EV technology is emerging day by day. Biggest challenge in front of OEM is the phase shift from ICE to EV. OEM need to decide on glide path for test rig development for this change to support ICE & EV powertrain validation to deliver reliable product to their customers. In EV development, major focus is on investment for battery development. Hence, for the Motor and Gearbox validation balanced approach is to upgrade existing ICE test bench for the EV with minimum effort and cost. This paper provides details on need and approach required to make the ICE test bench capable for EV powertrain validation. Proposed methodology helps to support both type of powertrain and have maximum utilization of the test bench.

This paper introduces a novel approach to automate PID calibration for closed-loop control systems and the creep control function in an electric vehicle. Through a comprehensive literature survey, it is found that this method is the first of its kind to be applied in the field of automated electric vehicle calibration for Creep function. The proposed approach utilizes a systematic methodology that automatically tunes the PID parameters based on predefined performance criteria, including energy consumption and jerk. To implement this methodology, the ETAS INCA FLOW software, which provides guided calibration methods for in-vehicle testing & calibration, is employed. The calibration process is performed on a real-time electric vehicle platform to validate the effectiveness of the proposed approach. The results of this study showcases the advantages of automated PID calibration for closed-loop control systems and creep control function in small commercial electric vehicle.

Global concerns over availability and environmental impact of conventional fuels in recent years have resulted in evolution of Electric Vehicles. Research and development focus has shifted towards one of its main components, Lithium-ion battery. Development of high performing, long lasting batteries within challenging timelines is the need of the industry. Lithium-ion batteries undergo “battery ageing”, limiting its energy storage and power output, affecting the EV performance, cost & life span. It is critical to be able to predict the rate of battery ageing & the impact of different environmental conditions on battery lifetime/capacity. Conventionally, extensive physical vehicle level testing is carried out on batteries to map the battery capacity in various conditions. This is a lengthy & expensive process affecting the product development cycle, paving the way for an alternative process.

Tire inflation pressure has a significant impact over vehicle driving dynamics, fuel consumption as well as tire life. Therefore, continuous monitoring of tire pressure becomes imperative for ride comfort, safety and optimum vehicle handling performance. Two types of tire pressure monitoring systems (TPMS) used by vehicles are - direct and indirect TPMS. Direct systems deploy pressure sensors at each wheel and directly send pressure value to the vehicle Controller Area Network (CAN). Indirect sensors on the other hand use the information from already existing sensors and some physics-based equations to predict the value of tire pressure. Direct TPMS tend to be more accurate but have higher cost of installation while indirect TPMS comes with a minimum cost but compromised accuracy. A digital proof-of-concept study for indirect TPMS development of a non-ESP vehicle based on machine learning (ML) technique is elaborated in this paper.

Polymer Electrolyte Membrane Fuel Cell (PEMFC) technology is considered for automotive applications due to rapid start up, energy efficiency, high power density and less maintenance. In line with National Hydrogen Energy Roadmap of Govt. of India that aims to develop and demonstrate hydrogen powered IC engine and fuel cell based vehicle. TATA Motors Ltd. has designed, developed and successfully demonstrated “Low Floor Hydrogen Fuel Cell Bus” which comprises of integrated fuel cell power system, hydrogen storage and dispensing system. The fuel cell power system, converts the stored chemical energy in the hydrogen to DC electrical energy. The power generated is regulated and used for powering the traction motor. The development of fuel cell bus consists of five stages: Powertrain sizing as per vehicle performance targets, fuel cell stack selection and balance of plant design and development, bus integration, hydrogen refueling infrastructure creation and testing of fuel cell bus.

Authors were challenged with a task of developing a full vehicle simulation model, with a target to simulate the electrical system performance and perform digital tests like Battery Charge Balance, in addition to the fuel efficiency estimation. A vehicle is a complicated problem or domain to model, due to the complexities of subsystems. Even more difficult task is to have a control algorithm which controls the vehicle model with the required control signals to follow the test specification. Particularly, simulating the control of a vehicle with a manual transmission is complicated due to many associated control signals (Throttle, Brake and Clutch) and interruptions like gear changes. In this paper, the development of a full vehicle model aimed at the assessment of electrical system performance of the vehicle is discussed in brief.

The AMT (Automated Manual Transmission) has attracted increasing interest of automotive researches, because it has some advantages of both MT (Manual Transmission) and AT (Automatic Transmission), such as low cost, high efficiency, easy to use and good comfort. The hill-start assistance is an important feature of AMT. The vehicle will move backward, start with jerk, or cause engine stalling if failed on the slope road. For manual transmission, hill-start depends on the driver's skills to coordinate with the brake, clutch and throttle pedal to achieve a smooth start. However, with the AMT, clutch pedal is removed and therefore, driver can’t perceive the clutch position, making it difficult to hill-start with AMT without hill-start control strategy. This paper discussed about the hill start control strategy and its functioning.

Micro Hybrid Systems are a premier approach for improving fuel efficiency and reducing emissions, by improving the efficiency of electrical energy generation, storage, distribution and consumption, yet with lower costs associated with development and implementation. However, significant efforts are required while implementing micro hybrid systems, arising out of components like Intelligent Battery Sensor (IBS). IBS provides battery measurements and battery status, and in addition mission critical diagnostic data on a communication line to micro hybrid controller. However, this set of data from IBS is not available instantly after its initialization, as it enters into a lengthy learning phase, where it learns the battery parameters, before it gives the required data on the communication line. This learning period spans from 3 to 8 hours, until the IBS is fully functional and is capable of supporting the system functionalities.

In a Mild hybrid electric vehicle, a battery serves as a continuous source of energy but is inefficient in supplying peak power demands required during torque assists for short duration. Moreover, the random charging and discharging that result due to varying drive cycle of the vehicle affects the life of the battery. In this paper, an Ultra-capacitor based hybrid energy storage system (HESS) has been developed for mild hybrid vehicle which aims at utilizing the advantages of ultracapacitors by combining them with lead-acid batteries, to improve the overall performance of the battery, and to increase their useful life. Active current-sharing is achieved by interfacing ultracapacitor to the battery through a bi-directional boost dc-dc converter.

Induction motor is very much used in mild hybrid vehicles because of its low cost, rugged structure and reliability. To test the induction motor controller in hardware-in-the-loop (HIL) simulation environment efficiently in both motoring and generating modes, generally, an instantaneous dynamic model of induction motor drive is used which requires the instantaneous values of PWM signals of inverter switches and hence a very high sampling frequency of about twenty times the switching frequency is required to effectively capture all the switching information of MOSFETS. This requires a HIL system with very powerful processor which increases the overall cost of system. In this paper, a dynamic average-value model of induction motor drive is developed in MATLAB/Simulink which requires only the duty cycle information instead of instantaneous switching information of PWM signals. Its performance is compared with the instantaneous model which is also developed in MATLAB/Simulink.

With the current state of ever rising fuel prices and unavailability of affordable alternate technologies, significant research and development efforts have been invested in recent times towards improving fuel efficiency of vehicles powered with conventional internal combustion engines. To achieve this, a varied approach has been adopted by researchers to cover the entire energy chain including fuel quality, combustion quality, power generation efficiency, down-sizing, power consumption efficiency, etc. Apart from energy generation, distribution and consumption, another domain that has been subjected to significant scrutiny is energy recuperation or recovery. A moving vehicle and a running engine provide a number of opportunities for useful back-recovery and storage of energy. The most significant sources for recuperation are the kinetic energy of the moving vehicle or running engine and to a lesser extent the thermal energy from medium such as exhaust gas.

On Board Diagnostics norms enforced by regulatory authorities of many countries require logging of distance traveled by the vehicle with MIL (malfunction indicator lamp) illuminated. This log needs to be maintained in non-volatile ECU memory. Conventional techniques maintain the log in a volatile memory during vehicle run-time and transfer the same to non-volatile memory when ignition is turned off. This requires use of a “power-hold” relay to keep an ECU power alive while the logged data in volatile memory is being transferred to non-volatile memory when ignition is switched-off. A novel strategy described in this paper avoids interface with power-hold relay, thereby reducing the system complexity. The design philosophy described makes use of an EEPROM to maintain the distance log. An innovative algorithm is employed to ensure that endurance specifications are not violated during the vehicle life-time.

Automotive embedded control systems need to implement real-time closed-loop control strategies for controlling valves, motors, etc. The implementation needs to focus on use of low cost hardware and efficient software with minimal foot-print so as to adequately meet the application requirement. This paper highlights the low cost hardware and software design concepts by way of a case study related to control of progressive EGR valve. The control strategy is based on "map-driven set-points" where percentage opening of the valve is stored in the form of 16x16 matrices. The set-points are accessed based on instantaneous throttle and engine rpm values which form the row and column indices of the map. The closed loop control algorithm eliminates the need for multiplication by implementing "feed-forward with integral control algorithm." A feed-forward map specifies the most likely PWM duty cycle to be applied to the valve for a given set-point.