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Original equipment manufacturers have already begun to transition their vehicles from traditional internal combustion engines (ICs) to electric drives (EVs). As the industry continues to move towards electrification, the entire industry, and especially Valeo, is focusing on lean product development (LPD) with the help of numerical simulation. Optimization techniques help industry achieve the most accurate product at the lowest cost without sacrificing performance. Generally gears are mainly used for power transmission in the advanced technologies of electric vehicles. There are many factors that must be taken into account when designing a gear transmission system. Finding the most appropriate design parameters for a gear transmission system can be a challenge, and optimization parameters will help to find the best compromise between them.

With the advent of electric and hybrid drivetrain in the commercial vehicle industry, electrically driven reciprocating compressors have gained widespread prominence. This compressor provides compressed air for key vehicle systems such as brakes, suspension systems and other auxiliary applications. To be a market leader, such an E-compressor needs to meet a myriad of design requirements. This includes meeting the performance by supplying air at required pressure and flow rate, durability requirements, oil free operation and having a compact design while maintaining cost competitiveness. The reed valve in such a compressor is a vital component, whose design is critical to meet the aforementioned requirements. The reed valves design has several key parameters such as the stiffness, natural frequency, equivalent mass, and lift distance which must be optimized. This reed valve also needs to open and close rapidly in response to the compressor operating speed.

Automotive radar plays a crucial role in object detection and tracking. While an standalone radar possesses ideal characteristics, integrating it within a vehicle introduces challenges. The presence of vehicle body, bumper, chassis, and cables in proximity influences the electromagnetic waves emitted by the radar, thereby impacting its performance. To address these challenges, electromagnetic simulations can guide early-stage design modifications. However, operating at very high frequencies around 77GHz and dealing with the large electrical size of complex structures demand specialized simulation techniques to optimize radar integration scenarios. Thus, the primary challenge lies in achieving an optimal balance between accuracy and computational resources/simulation time. This paper outlines the process of radar vehicle integration from an electromagnetic perspective and demonstrates the derivation of optimal solutions through RF simulation.

Most of the heavy commercial vehicles are installed with Pneumatic brake system where the medium is a pressurized pneumatic air generated with the reciprocating air compressor. Heating is an undesirable effect of the compression process during loading cycles as reciprocating air compressors are concerned. There fore it is necessary to reduce the delivery air temperature of compressor for safer operation of down stream products. The present investigation deals with the measurement of the delivery air tempearture of a typical 318 cc water cooled compressor. A through steady state conjugate heat transfer analysis is conducted for different speed and different cooling water flow rate to compare the delivery air temperature. Pressure drop across the cooling water flow path has been measured and optimum flow rate is arrived to meet the design requirement.

Artificial Intelligence (AI) and Machine Learning (ML) technologies have emerged as transformative forces across various domains, revolutionizing industries, and reshaping societal paradigms. In this work, we show how a CNN model was used in the field of CFD to predict drag coefficient of a full vehicle profile. A brief description is also provided of the data set used for training and fitting the prediction model. This was done using the integrated AI/ ML technology in the DEP MeshWorks tool focusing on quick design iterations and results generation. The design advisor function within MeshWorks is an intelligent system that comprehends the real-time prediction of the responses such as model stiffness, frequency and others related to durability, NVH or CFD domain, on a model building phase without needing to run the post-processing for every design iteration.

To ensure proper airflow distribution inside the cabin, the AC duct vanes' ability to direct airflow must be evaluated. Objective of this work is to propose a methodology for developing the vane design of AC system duct. CFD based factorial analysis was conducted using three components at three levels. The impact of number of horizontal vanes, number of vertical vanes and distance between them on the pressure drop and face level velocity are investigated. It was observed that when the number of vertical vanes are increased, the vane's ability to direct airflow rises. In this situation, the pressure drop increases as well. When the number of horizontal vanes exceeds a specific threshold, the vane's capacity to steer airflow declines. In literature, it can be noted that a greater number of research are available that focus on the relationship between human thermal comfort and vent position.

This paper investigates the condensation within a two wheeler instrument cluster in different weather conditions. Instrument cluster have high heating components within its assembly particularly over Printed Circuit Board (PCB) which leads to formation of condensation. Air breathers are important component that can be utilized to reduce the condensation in the cluster. Location and orientation of air breather and air vents plays the vital role in the air flow through the instrument cluster. In this study, number of breather and their location and orientation is optimized to reduce the condensation or film thickness on the crystal (transparent body) of cluster. Transient Computational Fluid Dynamics (CFD) based Eulerian Wall Film approach is utilized to investigate the physics administering the condensation phenomenon in the instrument cluster. Experimental tests are conducted to investigate condensation phenomenon actually occurring in the model.

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