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High currents flowing through various traces of a printed circuit boards (PCB) causes thermal run away and PCB warpage due to the occurrence of high heat density. The present study discusses on steady state thermal analysis performed in a PCB kept inside an enclosure. Thermal analysis allows PCB designer to quickly move and confirm the component’s placement by examining the temperature plots predicted on the PCB surface. A PCB particularly designed for automated manual transmission (AMT) application employed in Ashok Leyland electric vehicle (EV) trucks is used for this present study. The performed simulations are preliminary level and carried out with commercially available software Altair Simlab ElectroFlo 2022.3. Simlab is a PCB level EDA (Electronic Design Automation) software suite used for design and analysis, and thus helps in minimizing the development cycles.

In electric vehicles, Li-ion battery pack is the most expensive subsystem. Therefore, extending the life of the battery pack and thereby reducing the need for battery pack replacement is necessary to offer a viable product at a competitive cost of ownership. Thermal management of battery pack plays an important role in achieving the above mentioned objective since the performance and life of lithium ion batteries is greatly influenced by temperature. There are various thermal management strategies available to keep the temperature under control like air cooling, chilled liquid cooling and hybrid cooling systems. In this paper, a comparison between phase change material (PCM) and PCM/liquid hybrid cooling is made. The result of the study to understand the applicability of PCM for thermal management of Li-ion batteries is presented. CFD thermal analysis under constant electrical load of 1C rate is carried out.

Bogie-type suspensions for trucks are comprised of two axles and a central spring pack on each side of the truck chassis. Bogie suspensions have a good load distribution between the axles and are used for severe applications in trucks, in off-road conditions thereby subjecting them to extreme stain and load. In today’s competitive market scenario, it of utmost importance to minimize down time in commercial vehicles as it directly corresponds to loss in business which leads to customer dissatisfaction. It is therefore essential to optimize and select the right material for each component in the bogie suspension system. This paper deals with the material selection and testing of one such component - Bogie Wear Pad. The bogie wear pad undergoes sliding friction throughout its lifetime during loading and unloading of bogie suspension. Three different materials are selected and their wear is measured under the same conditions of loading.

The suspension system in a vehicle isolates the frame and body from road shocks and vibrations which would otherwise be transferred to the passengers and goods. Heavier goods vehicles use tandem axles at the rear for load carrying. Both the axles should be inter-connected to eliminate overloading of any one axle when this goes over a bump or a ditch. One of the inter-connecting mechanism used is leaf spring with tie rod, bell crank & linkages, when the first rear axle moves over a bump, the linkages equalize the loading on the second rear axle. This paper details about the failure analysis methodology to simulate the tie rod field failure using a six poster road simulator and to identify the root cause of the failure and further corrective actions.

All automotive components undergo stringent testing protocol during the design validation phase. Nevertheless, there are certain components in the field which are seldom captured during design validation. One of these components is the battery isolator switch. This project aims at optimizing a validation methodology for this component based on field usage and conditions. The isolator switch is the main control switch which connects and disconnects the electrical loads from the battery. This switch is used in the electrical circuit of the vehicle to prevent unwanted draining of battery when it is not needed and when the vehicle is in switched off. An electrical version of this switch uses electromagnetic coils to short the contacts. The failure mode being investigated is a high current load causing the input and output terminal to be welded.

In heavy commercial vehicle segment in India, driver comfort and feel was largely ignored. Fierce competition in the recent years and buyer’s market trend is compelling the designers of heavy truck to focus more on the finer aspects of attribute refinements. Steering is one driver-Vehicle interface which the driver is engaged throughout. Comfort and feel in steering wheel is defined by parameters like steering effort, manoeuvrability, on-center feel & response, cornering feel & response, Torque dead band, return-ability etc. and is influenced by a long list of components and systems in the truck. This study focuses on the influences of jacking torque and steering system friction on the on-center driving performance. Experiments to measure the Jacking torque and steering system friction were conducted in the lab and subjective and objective assessments of on-center driving performance were later conducted at test track in two similar 12 Ton truck to correlate their effects.

Steering wheel being the most used tactile point in a vehicle, its feel and response is an important factor based on which the vehicle quality is judged. Engineering the right feel and response into the system requires knowledge of the objective parameters that relate to the driver perception. Extensive correlation work has been done in the past pertaining to passenger cars, but the driver requirements for commercial vehicles vary significantly. Often it becomes difficult to match the right parameters to the steering feel experienced by the drivers, since most of the standard ISO weave test units used to describe them are of zero or first order parameters. Analyzing the second order parameters gave a better method to reason driver related feel. Also, each subjective attribute was fragmented into sub-attributes to identify the reason for such a rating resulting in the identification of the major subjective parameters affecting driver ratings.