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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 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.

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.

The need for effective control systems is exacerbated by tighter pollution regulations and consumer demands for highly efficiently vehicles especially in the passenger segment. The air flow estimation of engine and accordingly controlling the fuel removes the lacuna of modern gasoline engines. The hot wire type mass air flow sensor is commonly used for air flow measurement, and it generally mounted in clean side piping to prevent damage to air mass flow sensor. The right estimation of air flow is possible by getting uniform flow over the different engine operating speed and load conditions. The placement of air flow sensor becomes critical considering the engine layout and packaging constraints and meeting the sensor mounting requirements. The deviation in mounting of air flow sensor will lead to consequently impact of engine performance and emissions.

Electrical and Electronic systems in a vehicle are increasing manifolds with Electric and ADAS Vehicles taking the lead. There is a rapid transition happening from hardware driven vehicles to software driven vehicles. ISO 26262 is a global standard defined for functional safety (FuSa) in the automotive industry which addresses the structured design and development approach for eliminating electrical malfunctions leading to critical hazards such as fire in EVs. The standard defines specific requirements that need to be met by the safety relevant electrical system and also by development processes. Though the implementation of FuSa is crucial from vehicle safety point of view, its compliance is still a challenge majorly due to lack of awareness, in-built complexities, increase in project development time and subsequent cost. In this work, we focus on a FuSa implementation model taking into account the conventional new program development cycle.

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.

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.

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.

Today, most vehicles in developing countries are equipped with air conditioning systems that work with Hydro-Fluoro-Carbons (HFC) based refrigerants. These refrigerants are potential greenhouse gases with a high global warming potential (GWP) that adversely impact the environment. Without the rapid phasedown of HFCs under the Kigali Amendment to the Montreal Protocol and other actions, Earth will soon pass climate tipping points that will be irreversible within human time dimensions. Up to half of national HFC use and emissions are for the manufacture and service of mobile air conditioning (MAC). Vehicle manufacturers supplying markets in non-Article 5 Parties have transitioned from HFC-134a (ozone-safe, GWP = 1400; TFA emissions) to Hydro-Fluoro-Olefin, HFO-1234yf (ozone-safe, GWP < 1; TFA emissions) due to comparable thermodynamic properties. However, the transition towards the phasing down of HFCs across all sectors is just beginning for Article 5 markets.

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.

Twist-beam suspensions are an example of design solution presenting acceptable performance when applied to passenger cars & light vehicles and it can provide an optimal between cost & performance in the automotive market. For these reasons, twist beam is quite popular in use in rear suspension of light vehicles. In contrary to other types of suspension, the twist-beam has a flexible torsion beam connecting the swing arms. The study of the deformation of this flexible element becomes important to understand its performance and durability behavior. As the name signifies, twist beam major performance attribute is control of twist or opposite wheel travel arising from vehicle roll or road input. Current approach for the study this deformation is through FEA & Multi-body dynamics software tools.

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.

In an automotive braking system, Vacuum pump is used to generate vacuum in the vacuum servo or brake booster in order to enhance the safety and comfort to the driver. The vacuum pump operation in the braking system varies from conventional to electric vehicles. The vacuum pump is connected to the alternator shaft or CAM shaft in a conventional vehicle, operates continuously at engine speed and supplies continuous vacuum to the brake servo irrespective of vacuum requirement. To sustain continuous operation, these vacuum pumps are generally oil cooled. Whereas in electric vehicles, the use of a motor-driven vacuum pump is very much needed for vacuum generation as there is no engine present. Thus, with the assistance of an electronic control unit (ECU), the vacuum pump can be operated only when needed saving a significant amount of energy contributing to fuel economy and range improvement and emission reduction.

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).

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.

State of Charge (SoC) estimation of battery plays a key role in strategizing the power distribution across the vehicle in Battery Management System. In this paper, a model for SoC estimation using Extended Kalman Filter (EKF) is developed in Simulink. This model uses a 2nd order Resistance-Capacitance (2RC) Equivalent Circuit Model (ECM) of Lithium Ferrous Phosphate (LFP) cell to simulate the cell behaviour. This cell model was developed using the Simscape library in Simulink. The parameter identification experiments were performed on a new and a used LFP cell respectively, to identify two sets of parameters of ECM. The cell model parameters were identified for the range of 0% to 100% SoC at a constant temperature and it was observed that they vary as a function of SoC. Hence, variable resistance and capacitance blocks are used in the cell model so that the cell parameters can vary as a function of SoC.

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.

With the advent of BS VI regulations, automotive manufacturers are required to innovate the powertrains, fuel systems, exhaust and its after treatment systems to meet the regulatory requirements. The exhaust regulations can be met either by reducing the exhaust gases being generated by the engine (attacking the source) or by treating the exhaust gases in after treatment devices. The choice of the opted system varies with the manufacturer. The after-treatment devices such as catalytic converters are generally mounted in the engine compartment to take advantage of high temperature of exhaust gases to yield the reactions. Such an arrangement imposes a lot of thermal load on the peripheral components such as gearshift cables, bearings, oil seals, driveshafts etc. Thermal shields or thermal sleeve are used to address thermal issue and to protect transmission components.

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.