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The low running cost of electric two wheelers is resulting in high popularity and growing market share. The electric two wheelers are generally considered silent. However, the tonal nature of radiated noise is annoying for both driver and pedestrians in electric vehicles. This study focuses on electric two-wheeler with annoyance issue. The customer complained about non-linear noise with respect to speed and also whining during loading and coasting. The detailed Noise Source Identification (NSI) revealed that the noise is due to motor and transmission whine and structural resonances of chassis excited by this motor excitation during runup and gear whine orders during coasting when excitation by motor is absent. The motor mounting and chassis are structurally modified with suitable stiffeners and damping based on the results of modal analysis. The transmission gear geometry and contact pattern are optimized for transmission error reduction.

The technology development in automobiles is progressing towards providing smarter vehicles with increased efficiency and reduced emission. To cater this need, Electric Vehicles (EV) and Hybrid Electric Vehicles (HEV) are slowly thriving in Indian roads. Conversion of existing IC engine powered vehicle to HEV reduces complication in new vehicle development and also results in vehicles with increased efficiency and reduced emission. In order to convert the Conventional Vehicle to Hybrid Electric Vehicle, drive from electric motor was coupled with existing driveline by modifying mechanical systems suitably. Hybrid vehicle includes systems such as electric motors, inverters, high-voltage batteries and electronic control units, which are mounted in chassis members. Being a major load carrying member, any modifications in chassis system may affect the performance of vehicle, therefore it is necessary to evaluate the modified design of chassis members.

This paper introduces xEV Simulator- A MATLAB based simulator platform capable of analyzing EV/HEV powertrain system in both backward and forward modelling. xEV Simulator employs Forward Simulation for drive-cycle performance evaluations and Backward simulation for powertrain component sizing and support xEV powertrain design. The powertrain subsystems are modelled in Simulink. This enables the model based system simulation and further controller prototyping and HiL testing. xEV Offline Simulator GUI enables user to simulate standard EV/HEV configurations with standard drive-cycles. The model parameters of different component subsystems can be configured. The Backward modelling and simulation support the estimation of subsystem values like Propulsion motor, Energy storage, etc., to perform as per the drive-cycle requirement.

This paper presents a methodology for predicting thermal comfort inside Midibus cabin with an objective to modify the Heating, Ventilation and Air Conditioning (HVAC) duct design and parametric optimization in order to have improved thermal comfort of occupant. For this purpose the bus cavity is extracted from baseline CAD model including fully seated manikins with various seating positions. Solar Load has been considered in the computational model and passenger heat load is considered as per BSR/ASHRAE 55-1992R standard. CFD simulation predicted the air temperature and velocity distribution inside passenger cabin of the baseline model. The experimental measurements have been carried out as per the guidelines set in APTA-BT-RP-003-07 standard. The results obtained from CFD and Experimental test were analysed as per EVS EN ISO7730 standard and calculated occupant comfort in terms of thermal comfort parameters like Predicted Mean Vote (PMV) and Predicted Percentage Dissatisfied (PPD).

The paper talks about Quantification of Alertness for vision based Driver Drowsiness and Alertness Warning System (DDAWS). The quantification of alertness, as per Karolinska Sleepiness Scale (KSS), reads the basic input of facial features & behaviour recognition of driver in a standard manner. Although quantification of alertness is inconclusive with respect to the true value, the paper emphasised on systematic validation process of the system covering various scenarios in order to evaluate the system’s functionality very close to the reality. The methodology depends on definition of threshold values of blink and head pose. The facial features are defined by number of blinks with classification of heavy blink and light blink and head pose in (x, y, z) directions. The Human Machine Interface (HMI) warnings are selected in the form of visual and acoustic signals. Frequency, Amplitude and Illumination of HMI alerts are specified.

The Construction & Mining field is continuously upgrading, reshaping under the stimulus of technical enhancement. India is considered one of fastest growing country in the word. Requirement for Construction Equipment Vehicles in India is continuously growing due increased rate infrastructure development. To promote development of the Construction Equipment Vehicles (CEV’s) manufacturing sector it was also necessary to build a new governance architecture. Every vehicle plying on road has to comply with Central Motor Vehicle Regulatory requirements as per CMVR act 1989. Earlier 2021 CEV’s were required to go through performance trials like brake, steering effort, turning circle measurement, speedometer calibration as dynamic tests as per regulations.

India is one of the largest markets for the automobile sector and considering the trends of road fatalities and injuries related to road accidents, it is pertinent to continuously review the safety regulations and introduce standards which promise enhanced safety. With this objective, various Advanced Driver Assistance Systems (ADAS) regulations are proposed to be introduced in the Indian market. ADAS such as, Anti-lock Braking Systems, Advanced Emergency Braking systems, Lane Departure Warning Systems, Auto Lane Correction Systems, Driver Drowsiness Monitoring Systems, etc., assist the driver during driving. They tend to reduce road accidents and related fatalities by their advanced and artificial intelligent fed programs. This paper will share an insight on the past, recent trends and the upcoming developments in the regulation domain with respect to safety.

The Indian market for battery-powered electric vehicles (xEV) is growing exponentially in the coming years, fueled by tumbling lithium-ion battery prices and favorable government policies. Lithium-ion battery is leading in clean mobility ecosystem for electric vehicles. LiBs efficient and safe performance for tropical climatic conditions is one of the primary requirements for xEV to succeed in India. The performance of LiBs, however, is impacted due to ambient temperature as well as the heat generated within cell due to the load cycle electrochemical reaction. The acceptable operating temperature region for LiBs normally is between 20 °C to 45 °C and anything outside of this region will lead to degradation of performance and irreversible damages. Therefore, understanding the thermal behavior is very crucial for an efficient battery thermal management.

Autonomous vehicles perform various functions with their own control strategies. Functions like Lane Departure Warning (LDW), Lane Keeping system (LKS) and Forward Collision Warning System (FCWS) requires special test tracks for their verification and validation. These test track requirements change with region to region according to available infrastructure. This paper deals with the design and development of test tracks for different ADAS functions verification and validation of Indian specific scenarios and its simulation in IPG CarMaker. The test track conceptualization has been done through the understanding and study of different international standards and geometry of test tracks for Indian conditions have been developed. IPG CarMaker software tool is used for creation of test track, and same track is used for simulation of above ADAS functions in IPG CarMaker.

Battery is one of the safety critical systems in EV. As the number of EVs increases, battery safety becomes an important task to avoid any mishap during its use, as even small accidents may slow down the adaptation of EVs. Automotive environment being one of the harshest operating environments, it is important to ensure both mechanical and electrical safety of the battery pack. Li-Ion batteries are most popular among traction batteries, due to their high energy density, long life, and fast charging capabilities. But mechanical damage, over temperature, short-circuit, etc. may lead to battery thermal runaway, causing a major accident. Mechanical abuse of battery can be one of the reasons that may lead to the damages mentioned above, eventually causing thermal runaway in batteries. That’s why all major battery safety standards have requirements for vibration and mechanical shock tests.

In order to reduce development time and costs, application of numerical prediction techniques has become common practice in the automotive industry. Among the wide range of simulation applications, prediction of the vehicle interior noise is still one of the most challenging ones. The Finite Element Method (FEM) is well known for acoustic predictions in the low-frequency range. As part of the development of a full sized bus model, noise levels at Driver Ear Levels (DEL) and Passenger Ear Levels (PEL) were targeted. The structural and acoustic analysis were performed for a bus to reduce interior noise in the low-frequency range. Various counter measures were identified and structural optimization/modifications were performed from virtual simulation to reduce the DEL and PEL. Structure-borne noise due to both road-induced vibration and engine vibration were considered by using FEM techniques.

Recently, Hybrid electric vehicles have become significant. Electric vehicle is still in its infancy while grappling with multiple solutions to its problem of range anxiety and heavy weight. It makes HEV the viable and intermediate solution which can facilitate the transition. The battery behaviour is grossly defined by its dependence on variation due to temperature change. Hence, this present work focuses on understanding thermal characterization & pure behaviour of the Li-Ion Phosphate (LiFePO4) P1-HEV battery using the HPPC test. This becomes imperative because of the varying driver demands and ambient temperatures over the use during the day. Thus, the current drawn from battery varies (different C rate) leading to heat generation (I2R heating) within the pack/individual cell. Cyclically, impacting the cell performance and battery cycle life.