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Vehicle incab booming perception, a low frequency response of the structure to the various excitations presents a challenging task for the NVH engineers. The excitation to the structure causing boom can either be power train induced, depending upon the number of cylinders or the road inputs, while transfer paths for the excitation is mainly through the power train mounts or the suspension attachments to the body. The body responds to those input excitations by virtue of the dynamic behavior mainly governed by its modal characteristics. This paper explains in detail an integrated approach, of both experimental and numerical techniques devised to investigate the mechanism for boom noise generation. It is therefore important, to understand the modal behavior of the structure. The modal characteristics from the structural modal test enable to locate the natural frequencies and mode shapes of the body, which are likely to get excited due to the operating excitations.

Battery Thermal management is a major challenge for occupant safety in an electric vehicle. Predicting the battery electrical losses and thermal behaviour is another challenge for the battery management system. Different virtual models are developed for cell level and pack level thermal evaluation. All these models have a varying degree of accuracy and limitation. The latest developed model is more accurate and can predict the battery cell & pack level temperatures. The battery can be modeled in different ways, ECM (Electrochemical model), EIS (Electrochemical Impedance Spectroscopy) [1]. Newman model is a well-known electrochemical model. [2]. EIS uses a combination of DC and small AC signal [3,4]. ECM model also used for estimating SOC and in BMS [5]. The cell temperature in the battery pack not only depends upon the cell inside physics but also depends upon cell outside cooling physics. Cell outside physics is simulated by 3D CFD software during the design process [6].

Micro Hybrid Systems are a premier approach for improving fuel efficiency and reducing emissions, by improving the efficiency of electrical energy generation, storage, distribution and consumption, yet with lower costs associated with development and implementation. However, significant efforts are required while implementing micro hybrid systems, arising out of components like Intelligent Battery Sensor (IBS). IBS provides battery measurements and battery status, and in addition mission critical diagnostic data on a communication line to micro hybrid controller. However, this set of data from IBS is not available instantly after its initialization, as it enters into a lengthy learning phase, where it learns the battery parameters, before it gives the required data on the communication line. This learning period spans from 3 to 8 hours, until the IBS is fully functional and is capable of supporting the system functionalities.

In a Mild hybrid electric vehicle, a battery serves as a continuous source of energy but is inefficient in supplying peak power demands required during torque assists for short duration. Moreover, the random charging and discharging that result due to varying drive cycle of the vehicle affects the life of the battery. In this paper, an Ultra-capacitor based hybrid energy storage system (HESS) has been developed for mild hybrid vehicle which aims at utilizing the advantages of ultracapacitors by combining them with lead-acid batteries, to improve the overall performance of the battery, and to increase their useful life. Active current-sharing is achieved by interfacing ultracapacitor to the battery through a bi-directional boost dc-dc converter.

The objective of the work presented in this paper is to provide an overall CFD evaluation and optimization study of cabin climate control of air-conditioned (AC) city buses. Providing passengers with a comfortable experience is one of the focal point of any bus manufacturer. However, detailed evaluation through testing alone is difficult and not possible during vehicle development. With increasing travel needs and continuous focus on improving passenger experience, CFD supplemented by testing plays an important role in assessing the cabin comfort. The focus of the study is to evaluate the effect of size, shape and number of free-flow and overhead vents on flow distribution inside the cabin. Numerical simulations were carried out using a commercially available CFD code, Fluent®. Realizable k - ε RANS turbulence model was used to model turbulence. Airflow results from numerical simulation were compared with the testing results to evaluate the reliability.

This paper describes the Common Automobile Program (CAP) that can be implemented to improve mass transportation. CAP is the use of automated electric vehicles using smart navigation and control technologies to improve mass transportation. In CAP, common vehicles are used by different passengers, thus, reducing the on-road traffic and also the parking space required. Various low-cost stations are to be built along specified paths and the vehicle can be used at the convenience of the commuter. Currently, buses and trains require the passengers to wait at the station and a significant amount of time is spent at intermediate stops. The vehicle in CAP runs directly from origin to destination and also eliminates the waiting time at stations. Passengers do not wait for vehicles; instead vehicles wait for the passengers. The journey starts as the passenger enters the station and selects the destination.