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The Indian continental region encompasses various geographical terrains and climatic conditions, which necessitates automotive OEMs to build robust cabin climate control systems that ensure year round occupant comfort. Such systems comprise of, an on-board Heating Ventilation Air Conditioning (HVAC) sub-system and a control head (manual or automatic) that works as a user interface for adjusting parameters such as airflow, temperature and air directivity best suited to the occupants. In case of passenger cars, the on board HVAC system primarily serves two major purposes. To provide year round thermal comfort to the passengers and to enable defogging and defrosting action of front and rear windshield as per regulatory requirements and customer needs particularly for enhancing visibility in cold and humid ambient conditions.

Hybridization with engine downsizing is a regular trend to achieve fuel economy benefits. However this leads to a development of new downsized engine which is very costly and time consuming process, also engine downsizing demands for expensive higher power electric system to meet performance targets. Various techniques like gear ratio optimization, reducing number of gears, battery size and control functionalities optimization have been evaluated for maximum fuel economy keeping system cost very low and improving vehicle performance. With optimized gear ratios and reduced number of gears for parallel hybrid, it is possible to operate the engine in the best efficiency zones without downsizing. Motor is selected based on power to weight ratio, gradient requirements, improved acceleration performance and top speed requirement of vehicle in EV mode.

Reckoning today's environmental rules, legislative regulation and market requirements- the automotive industry of late has witnessed an increased vigor and enthusiasm by auto makers towards electrification of vehicles across all platforms in a bid to improve fuel economy and performance. Hybridization of a vehicle often involves the use of expensive high performance motors and large battery packs. However due to the challenges associated with the packaging of bulky battery and motor systems in existing drive train, mild hybrid systems have been preferred over strong or full hybrids especially in current production models as they don't entail any major change in architecture and the reduced battery size, both of which provide for easier packaging of components.

Transmission designs over the years have evolved significantly achieving more efficiency in terms of fuel economy, comfort and reduction in emissions. This paper describes a Dc motor based E-shift mechanism which automates an existing manual transmission and clutch system to give comfort and ease for gear shifting. The basic idea of E-shift mechanism is to make hassle free gear shifting of manual transmission at sole command of driver without any control strategy for automatic shifting as in case of Automated Manual transmission (AMT). The E-shift mechanism will eliminate the manual efforts required for pressing clutch pedal and shifting gear, giving more ease while driving. The developed mechanism can be retro fitted on existing manual transmission without any major modification at lower cost. The E-shift mechanism uses two actuators for gear shifting and one actuator for clutch actuation.

The OEM's aim is to reduce development time and testing cost, hence the objective behind this work is to achieve a flexible stateflow model so that changes in the application during supply chain or development, on adding/deleting any switches, varying timer cycle, changing the logic for future advancements or else using the logic in different application, would end in minimal changes in the chart or in its states which would reflect least changes in the code. This research is about designing state machine architecture for chime/buzzer warning system and wiper/washer motor control system. The chime/buzzer stateflow chart includes various input switches like ignition, parking, seat belt buckle, driver door and speed accompanied with warning in the form of LED, lamp and buzzer. The logic is differentiated according to gentle and strong warning. Various conditions and scenarios of the vehicle and driver are considered for driver door and seat belt which is resolved in the chart.

Leaf springs are used for vehicle suspension to support the load. These springs are made of flat sections of spring steel in single or in stack of multiple layers, held together in bracketed assembly. The key characteristics of leaf spring are defined as ability to distribute stresses along its length and transmit a load over the width of the chassis structures. The most common leaf spring steels are carbon steels alloyed with Cr and micro-alloyed with Ti, V and Nb. The specific thermomechanical process and alloying elements result in specific strength and fatigue properties for spring steels. The unique properties which facilitate use of spring steel in leaf spring suspensions are ability to withstand considerable twisting or bending forces without any distortion. The microstructure of these steel determines the performance and reflects the process of steel manufacturing. The performance is mainly determined by evaluating fatigue life durability.

A lightweight multi-material combination of steel and aluminium alloy (Al) is becoming a novel approach towards environmentally sustainable transport systems. Studies show that 10% reduction of vehicle weight results into 3-7% reduction in specific fuel consumption in IC engines and a 13.7% improvement in electric range for electric vehicles. However, dissimilar welding of Al/steel is a key challenge because of incompatible thermo-physical properties (melting point, thermal conductivity, and coefficient of thermal expansion) and low miscibility between Al and steel. The formation of brittle and hard Al-steel intermetallic compound (IMC) at the joint interface is the major concern for dissimilar welding of Al/steel. In this work, efforts are made to check the feasibility of Ni interlayer to control IMC formation at the interface of Al/steel dissimilar welded joint. Resistance spot welding is used to join low carbon steel CR01 and Al AA6061-T6 with pure Ni interlayer.

The Common Rail fuel injection System (CRS) has completely changed the whole diesel engine combustion cloud dynamics and enhanced the applicability of diesel engines further with a motto of providing a more cleaner sky and greener earth. The most cutting-edge technological developments made in CRS and EGT system enables OEMs to achieve further more stringent emission norms and adopt the environmental protection compliances. Today’s CRS systems are the most advanced generation fuel injection systems providing further high injection pressures, wide multiple injections capability with shorter dwell periods enabling real smoother Digital Rate Shaping (DRS) and injection control that benefits not only the engine combustion performance but also enables smarter thermal management of modern exhaust systems while meeting stringent emission compliances and achieving future CO2 reductions goal.

In an automotive air conditioning system, evaporator is well designed for effective heat transfer between refrigerant and air flowing over the evaporator. This cold and dehumidified air obtained at evaporator is then supplied to passenger cabin. There are various parameters like air flow over evaporator, ambient temperature, humidity condition and condensate drain mechanism which can cause frost formation over the evaporator core. This study presents the probable causes of frost formation and their effects on the performance of evaporator and thus affecting overall performances of the automotive air conditioning system. In this study effect of variation in four major independent factors such as poor response of thermistor, undercharged refrigerant system and overcharged refrigerant system, drop in air flow by blower due to clogged air-filter, and also the effect of type of compressor has been studied.

Various vehicle manufacturers are launching electric vehicles, which are more sustainable and environmentally friendly. The major component in electric vehicles is the battery, and its performance plays a vital role. Usually, the end of life of a battery in the automobile sector is when the battery capacity reaches 80% of its maximum rated capacity. The capacity of a lithium-ion cell declines with the number of cycles. So, a semi-empirical model is developed for estimating the maximum stored capacity at the end of each cycle. The parameters considered in the model explain the changes in battery internal structure, like capacity losses at different conditions. The capacity estimated using the semi-empirical model is further taken as the inputs for estimating capacity using the Artificial Neural Network (ANN) and Machine Learning (ML) techniques i.e., Linear Regression (LR), Gaussian Process Regression (GPR), Support Vector Machine methods (SVM).

This paper is an application of ISO 26262 functional safety standards for fail-safe design, development and validation of Electric Power Assisted Steering (EPAS) System. As part of safety feature to save lives, prevent injuries and reduce economic loss due to accidents, many research institutes are working to ensure the safety and reliability of emerging safety-critical Electronic Control Systems in automobile applications. As, Advanced Driver Assistance Systems (ADAS) and other emerging technologies are introduced in the automobile application, the overall safety of these advanced electronic systems relies on the vehicle safety systems, such as steering systems. This paper outlines the approach of performing the Hazard Analysis & Risk Assessment (HARA) and developing a Functional Safety Concept. This approach incorporates several analysis methods, including Hazard and Operability study, Functional Failure Modes and Effects Analysis.

The automotive industry has achieved remarkable advances in passenger car safety systems to mitigate the risk of injuries and fatalities caused by road accidents. However, to further improve vehicle safety, it is essential to have a deeper understanding of real-world accidents and the true safety benefits of various safety systems in the field. This requires a framework to evaluate the effectiveness of safety systems in reducing occupant injury and fatalities. This study aims to use machine-learning techniques to predict occupant injury severity by considering accident parameters and safety systems, using the Road Accident Sampling System - India (RASSI) real-world accident data. The RASSI database contains comprehensive accident data, including various factors that contribute to occupant injury. The study focused on fifteen accident parameters that represent key aspects of crash scenarios such as vehicle type, accident type, vehicle speed, and occupant details.