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The global and Indian automotive industry is transitioning from use of Internal Combustion Engine (ICE) vehicles towards Battery Electric Vehicles (BEVs). BEV applications with high voltage (HV) battery require optimal thermal management to have a longer life, higher efficiency and to deliver superior year-round performance. In most electric vehicles, the Heating Ventilation and Air Conditioning (HVAC) system operates thru a dual loop; one loop for maintaining desired cabin comfort and a second loop to ensure optimum cell temperature for HV battery operation at varying climatic conditions, which the vehicle experiences over different seasons of the year This paper evaluates the limitations of a baseline system, in which the HVAC system consists of two parallel low-pressure cooling lines, one for maintaining cabin comfort and another for the purpose of battery cooling.

Driving dynamics performance is one of the key customer attributes to be developed during product development. In the vehicle development process, freezing the hardware of the chassis aggregates is one of the major priorities to kick off the other vehicle development activities. The current work involves the development of a multilink suspension for an SUV class vehicle. Typically, each OEM performs several product development loops for maturing the vehicle design. The driving dynamics performance evaluation and tuning happens on a physical vehicle with the driver in Loop. Tuning of suspension parameter on the physical vehicle entails actual replacement of parts/components. This encompasses multiple tuning cycles in product development associated with increased cost and test time. To reduce the product development time and cost while delivering first time right chassis configuration, we took an approach of getting driver-in-loop through driving simulator in the concept phase.

In previous work, AC Compressor Cycling (ACC) was modeled by incorporating evaporator thermal inertia in Mobile Air Conditioning (MAC) performance simulation. Prediction accuracy of >95% in average cabin air temperature has been achieved at moderate ambient condition, however the number of ACC events in 1D CAE simulation were higher as compared to physical test [1]. This paper documents the systematic approach followed to address the challenges in simulation model in order to bridge the gap between physical and digital. In physical phenomenon, during cabin cooldown, after meeting the set/ target cooling of a cabin, the ACC takes place. During ACC, gradual heat transfer takes place between cold evaporator surface and air flowing over it because of evaporator thermal inertia.

In the context of vehicular safety and performance, brake pads represent a critical component, ensuring controlled driving and accident prevention. These pads consist of friction materials that naturally degrade with usage, potentially leading to safety issues like delayed braking response and NVH disturbances. Unfortunately, assessing brake pad wear remains challenging for vehicle owners, as these components are typically inaccessible from the outside. Moreover, Indian OEMs have not yet integrated brake pad life estimation features. This research introduces a hybrid machine learning approach for predicting brake pad remaining useful life, comprising three modules: a weight module, utilizing mathematical formulations based on longitudinal vehicle dynamics to estimate vehicle weight necessary for calculating braking kinetic energy dissipation; and temperature and wear modules, employing deep neural networks for predictive modeling.

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.

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.

With the introduction of Connected Vehicles, it is possible to extend the limited horizon of vehicles on the road by collective perceptions, where vehicles periodically share their information with other vehicles and servers using cloud. Nevertheless, by the time the connected vehicle spread expands, it is critical to understand the validation techniques which can be used to ensure a flawless transfer of data and connectivity. Connected vehicles are mainly characterized by the smartphone application which is provided to the end customers to access the connectivity features in the vehicle. The end result which is delivered to the customer is through the integrated telematics unit in the vehicle which communicates through a communication layer with the cloud platform. The cloud server in turn interacts with the final application layer of the mobile application given to the customer.

The automotive world is moving towards electric powertrain systems. The electric powertrain systems have emerged as a promising alternative to the conventional powertrain system. The performance of electric vehicle is highly dependent on operating temperature of electric and electronic components of the vehicle. All power electronics and electric components in EV generate heat during operation and it must be removed to prevent overheating of components. Higher temperatures raise safety concerns whereas lower temperatures deteriorate the performance of power electronics & electric components. These power electronics & electrical components perform efficiently and safely if operated within certain temperature range. This paper presents an advanced efficient cost-effective thermal technique for small commercial electric vehicle (SCEV) to improve the performance & life of major electric components.

As the automobile industry in India is growing fast and competitive, there is a need to design the vehicle and its parts at most cost effective. This paper gives the details of design optimization and cost effective methodology followed to develop a Single Stalk Combination Switch, without degrading the end user delight. This paper describes various design criteria affecting the combination switch design.

Today's automotive industry demands high quality component as well as system designs within very short period of time to provide more value added features to customers on one hand and to meet stringent safety standards on the other. To reconcile economy issues, design optimization has become a key issue. In the last few decades, many OEMs took to analytical tools like Computer-Aided-Engineering (CAE) tools in order to decrease the number of prototype builds and to speed up the time of development cycle. Although such analytical tools are relatively inexpensive to use and faster to implement as compared to the costly traditional design and testing processes: however, there are many variables that CAE tools cannot adequately consider, such as manufacturing processes, assembly, material anisotropy and residual stresses. Therefore, still smart measuring and testing techniques are required to substantiate the CAE results.

Battery cooling system plays a vital role in all kind of Electric vehicles. For Indian applications where vehicles will be subjected to slower speeds due to heavy traffic, higher ambient conditions and excess loading pattern in commercial vehicles, designing a Battery cooling system (BCS) is a challenging task. There are various options for cooling of battery i.e. Natural air cooled, forced air cooled, indirect cooling. This paper discusses about indirect coolant based cooling of battery of a small commercial vehicle. Battery cooling system works on the principle of Indirect cooling with the combination of vapor compression cycle and water-coolant mixture path. R134a gas used for VCRS system and for cooling system used 50-50% water glycol coolant mixture. For this type of battery cooling system typically There are challenges of packaging of various battery cooling parts, hose routing, pipe bends which may result in de aeration issues.

EU directive 2005/64/EC on type approval of motor vehicles with respect to their Reusability, Recyclability and Recoverability ( RRR ) requires vehicle manufacturers to put in place the necessary arrangements and procedures for Parts, Materials and Weight (PMW ) data collection from full chain of supply. This is required to perform the calculations of recyclability rate and recoverability rate in line with ISO 22628. Commonly practiced data collection methodologies included spreadsheet and use of internationally available IT support system for collection of material data. Data complexity and prohibitive cost for using Internationally available IT Support systems like IMDS (International Material Data System) has led to the in-house development of IT enabled Solution customizing Siemens PLM software product (Team centre Enterprise) and SAP (SRM suite).

The necessity of hybrid vehicles and electric vehicles is well known by now for reasons like fossil fuel depletion, climate change, emission norms mandated by regulations etc. With the addition of electric motor, battery and associated power electronics, the cost of powertrain and hence the vehicle goes up, which is often a hindrance for OEMs and end-customers. With the objective to make a cost-effective strong hybrid, Tata Motors has approached this problem by taking economies of scale approach i.e. developing an add-on gearbox module, which can fit a family of cars, in a P3-off axis hybrid configuration to an electrically actuated AMT. This paper presents the preliminary simulations, which show this architecture yielding a reduction of fuel consumption by ~20% for a B-class sedan/compact SUV of ~1800kg and ~15% improvement in acceleration performance. Additionally, the design and packaging studies show the fitment possibility in a highly congested powertrain bay.

Durability is an important indicator to measure the automobile quality and reliability. Automotive industry is striving to develop products having excellent performance to weight ratios and along with high safety standards. A successful product should have adequate robustness during normal customer operation and the ability to withstand high impact events without impairment of function or safety relevant damage. Road Load Data Acquisition (RLDA) along with efficient design and validation processes are, among others, critical factors for success in the automotive industry. Physical RLDA is expensive and time consuming, the prototype vehicles being costly and only available at a later stage in the vehicle development cycle. Component failures occurring on the proto test vehicles can prove to be a major setback, delaying the product launch by months. In order to overcome above challenge, this paper presents an innovative methodology to carry out Digital RLDA (dRLDA).

Regular vehicle has the advantage of Engine resistance even when it is not fired, hence chances of vehicle roll back on gradients will be minimized. This is not the case for Electric vehicles, which uses an electric motor that does not have any resistance offered to wheels that prevent vehicle roll back on gradient. This leads to increased load on the conventional hydraulic brakes due to absence of engine inertia. Hence, there is a need for a low cost and reliable automatic braking system which can help in holding the vehicle and assists the driver during launch in case he need to stop at a gradient. An Electromagnetic brake (EM brake) system can be used as a solution for the above-mentioned requirement. EM brake can provide hill hold and hill assist effect in addition to automatic parking brake application when the vehicle is turned-off. This system will assist anyone who need to halt the vehicle at a gradient and then relaunch it without much struggle.

In the recent years, Hybrid and Electric Vehicles (EVs) have gained attention globally due to conventional non-renewable fuels becoming expensive and increasing pollution levels in the environment. Li-ion battery EV’s are most popular because of their better power density, spe. energy density and thermal stability. With the advent of battery EV’s, concerns regarding thermal safety of vehicle and its occupants has grown among the prospective customers. Temperature plays an important role in the performance of the Li-ion battery which includes cell capacity, charge output, vehicle range, mechanical life of the battery etc. For Li-ion cells, optimum operating range should be between 15-35 °C [1], and all cells must also be maintained within a ±5 °C variation band. Computational Fluid Dynamics (CFD) simulation can be used to get better insight of cell temperature inside battery. But CFD simulation process is complex, time consuming involving multi-physics and exhaustive computations.

Transportation has significant and long-lasting economic, social and environmental impacts which makes it an important dimension of urban sustainability. The World is witnessing rapid changes in modern traveling behavior, and efforts are continuously being made to stimulate sustainable mobility solutions with smart policies, new business models, and advanced technologies (connected cars, sensors, electrification). However, the shift is gradual in India when compared to developed countries due to unique barriers to emerging green mobility solutions. This paper empirically investigates public travel satisfaction and the primary factors for the selection of modes for different types of commutes. Quantitative data were collected including socio-demographic, travel mode choices, and preferred future mobility solutions from the western states of India.

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).

Interdependency of automotive transmission aggregates on electrical/ electronics systems is increasing day by day, offering more comfort and features. For a system integrator, it becomes very much important while selecting/designing any such component to take into consideration the relationship between such interdependent components from performance as well as endurance point of view. DMF failures due to inadequate starting system, is a major stumbling block in development of DMF for a particular vehicle application. The interface of DMF and starting system of a vehicle makes it essential to consider the effect of one on another. The study shows that the majority of DMF failures happen because of resonance phenomenon in the DMF during engine starting. The improper selection of starter motor makes the DMF more vulnerable for such failures.

The public transport in India is gradually shifting towards electric mobility. Long range in electric mobility can be served with High Voltage Battery (HVB), but HVB can sustain for its designed life if it’s maintained within a specific operating temperature range. Appropriate battery thermal management through Battery Cooling System (BCS) is critical for vehicle range and battery durability This work focus on two aspects, BCS sizing and its coolant flow optimization in Electric bus. BCS modelling was done in 1D CAE software. The objective is to develop a model of BCS in virtual environment to replicate the physical testing. Electric bus contain numerous battery packs and a complex piping in its cooling system. BCS sizing simulation was performed to keep the battery packs in operating temperature range.