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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.

The primary function of an engine mounting bracket is to support the powertrain system in all road conditions without any failure. The mount has to withstand different road conditions and driving maneuvers which exert loads on it. Also, it is challenging to change the mounting locations and types after the engine is built; hence it is paramount to verify the mounting brackets against all abuse loads in the design stage. The Car manufacturers ensure engine mount bracket design meets CAE's (Computer-aided engineering) static and fatigue load cases. The CAE is performed using digital RLD (Road load data) loads. The design checks cumulative strain or stress against specified service life requirements during break and fatigue FOS (Factor of safety) calculations. However, it is difficult to simulate the material's fracture toughness to estimate the effect of the impact load on the mounting bracket.

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 commercial vehicle sector (especially trucks) has major role in economic growth of a nation. With improving infrastructure, increasing number of commercial vehicles and growing amount of Vulnerable Road Users (VRUs) on roads, accidents are also increasing. As per RASSI (Road Accident Sampling System India) FY2016-21 database, commercial vehicles are involved in 43% of total accidents on Indian roads. One of the major causes of these accidents is Driver Drowsiness and Inattention (DDI) (approx. 10% contribution in total accidents). This paper describes novel driver-in-loop performance assessment methodology for comprehensive verification of Driver Monitoring System (DMS) for commercial vehicle application. Novelty lies in specification of test subjects, driving styles and variety of road traffic scenarios for verification of DMS system. Test setup is made modular to cater to different platform environments (Heavy, Intermediate, Light) with minor modifications.

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.

Traditionally, vehicle ride and comfort is evaluated, subjectively as well as objectively. Based on the outcome of subjective and objective tests, it is refined by optimizing primary suspension system, secondary suspension system, seating system, rubber bushings, frame and BIW for mass, stiffness, damping, geometry etc. Many a time subjective assessment results stands in contradiction to the objective assessment results; emphasizing need for having good correlation between subjective and objective test results. In such cases, it is ambiguous to decide suitable design refinement action and can lead to no improvement situation. Hence, it is essential to have concurring test procedures for subjective and objective ride evaluation. This paper describes a novel methodology to address the above said challenge. There are defined set of test events and measurement data points to be used in subjective and objective testing.