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Technical Paper

Predicting Full Vehicle Drag Coefficient using a Convoluted Neural Network Approach

2024-10-17
2024-28-0007
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.
Technical Paper

Development of ANFIS Predictive Model for Additive Manufacturing (Fusion Deposition Modeling) of TPU Material

2024-10-17
2024-28-0025
Additive Manufacturing (AM) techniques, particularly Fusion Deposition Modeling (FDM), have received considerable interest due to their capacity to create complex structures using a diverse array of materials. The objective of this study is to improve the process control and efficiency of Fused Deposition Modeling (FDM) for Thermoplastic Polyurethane (TPU) material by creating a predictive model using an Adaptive Neuro-Fuzzy Inference System (ANFIS). The study investigates the impact of FDM process parameters, including layer height, nozzle temperature, and printing speed, on key printing attributes such as tensile strength, flexibility, and surface quality. Several experimental trials are performed to gather data on these parameters and their corresponding printing attributes. The ANFIS predictive model is built using the collected dataset to forecast printing characteristics by analyzing input process parameters.
Technical Paper

Towards automation of reference data generation for ADAS/AD functions development – ALiVA framework

2024-10-17
2024-28-0022
The advancements towards autonomous driving have propelled the need for reference/ground truth data for development & validation of various functionalities. Traditional data labelling methodologies are time consuming, skills intensive & have many drawbacks. These challenges are addressed through ALiVA (automatic lidar, image & video annotator), a semi-automated framework assisting for event detection & reference data generation through annotation/labelling of video & point-cloud data. ALiVA is capable of processing large volumes of camera & lidar sensor data. Main pillars of framework are object detection-classification models, object tracking algorithms, cognitive algorithms & annotation results review functionality. Automatic object detection functionality generates precise bounding box around the area of interest & assigns class labels to annotated objects.
Technical Paper

Unlocking radar sensor integration in vehicle: Accelerated product development harnessing electromagnetic simulation

2024-10-17
2024-28-0019
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.
Technical Paper

Parametric Solid Meshing of Tires

2024-10-17
2024-28-0017
CAE has been a critical tool for efficient tire development with the use of simulation to evaluate durability, drag and other performance metrics. A significant challenge in the process can be the significant amount of time consumed in setting up a tire model. Of late tire suppliers in Japan have been successfully using innovative ideas and tools to reduce this time by as much as 80 percent. The time savings translates to substantial reduction in turnaround time for evaluating new tire designs. They have been using custom CAE software that has inbuilt tools offering many useful features for any tire CAE team. There is a Hex meshing tool that gives the ability for the CAE engineer to generate a ‘pure’ quad mesh pattern across the tire cross-section along with the ability to automatically create a REBAR (internal reinforcement) layer within the tire. Hex meshes are desired for simulation as they offer better quality of results when compared to tetra meshes.
Technical Paper

ADAS Camera system validation using open-source maps data

2024-10-17
2024-28-0031
Advanced Driver Assistance Systems is a growing technology in automotive industry, intended to provide safety and comfort to the passengers with the help of variety of sensors like radar, camera, LIDAR etc. The camera sensors in ADAS used extensively for the purpose of object detection and classification which are used in functions like Traffic sign recognitions, Lane detections, Object detections and many more. The development and testing of camera-based sensor involves the greater technologies in automotive industry, especially the validation of camera hardware and software. The testing can be done by various process and methods like real environment test, model-based testing, Hardware and Software in loop testing. A fully matured ADAS camera system in the market comes after crossing all these verification process, yet there are lot of new failures popping up in the field with this ADAS system.
Technical Paper

Enhancing Gear Performance: Discrete Response Optimization through OptiSLang

2024-10-17
2024-28-0040
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.
Technical Paper

Enhancing the safety and handling of virtual vehicles in simulated traffic: A co-simulation approach with Multibody dynamics & Carla

2024-10-17
2024-28-0026
In recent years, there has been an increased emphasis on autonomous driving technologies to improve vehicle road safety amidst rising traffic congestion and the complexities of intersection, jaywalking and diverse road conditions. Therefore, improving the vehicle's handling ability is crucial for safe and efficient traffic navigation, particularly emphasizing collision prevention and safety in unforeseen circumstances. Evaluating safety perspectives in such situations, the lane change event serves as an important measure for addressing the matter and forms the focus of this paper. However, for such new age technology conducting proving ground tests replicating urban conditions is a costly endeavour. Hence, simulation is a better approach which can mimic real traffic conditions, develop control systems, and simulate vehicle handling behaviour, all working together within a closed-loop system.
Technical Paper

Design and Development of a Micromobility Smart Electric Scooter to Revolutionize Urban Commuting

2024-10-17
2024-28-0021
Urban areas around the world are facing an increasing number of issues, such asair pollution, parking shortages, traffic congestion, and inadequate transit options, all of which necessitate innovative solutions. Lot of people are becoming interested in micromobility in urban areas as a replacement for quick excursions and round trips to get to or from transportation services (e.g., Offices, Institutions, Hospitals, Tourist spots, etc.). This research examines the critical role that micromobility plays, concentrating on the effectiveness of micromobility smart electric scooters in resolving urgent urban problems. Micromobility which includes both human and electric-powered vehicles presents a viable substitute for normal and short-distance urban commuting. This study presents a micromobility smart electric scooter that is portable and easy to operate, with the goal of transforming urban transportation. 3D model was designed using SOLIDWORKS and analysed using ANSYS.
Technical Paper

Numerical And Experimental Investigation Of Water Cooled Reciprocating Air Compressor Used in Automotive Applications

2024-10-17
2024-28-0014
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.
Technical Paper

Synergistic 1-D and 3-D Analysis to Optimize the Performance and Reliability of the Reed Valve used in Reciprocating E-Compressor

2024-10-17
2024-28-0013
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.
Technical Paper

Design Optimization of Heat Transfer in Automotive Battery Using Generalized Neural Network Regression

2024-10-17
2024-28-0024
Electrification is driving the use of batteries for a range of automotive applications, including propulsion systems. Effective management of thermal energy in lithium-ion battery pack is essential for both performance and safety. In automotive applications especially, understanding and managing thermal energy becomes a critical factor. Cells in the propulsion battery pack dissipate heat at high discharge rates. Cooling performance of battery can be realized by optimizing the various parameters. Computational Fluid Dynamics (CFD) model build and simulations are resource intensive and demands high performance computing. Traditionally, evaluating thermal performance involves time-consuming CFD simulations. To address this challenge, the proposed novel approach using Generalized Neural Network Regression (GNNR) eliminates complex CFD model building and significantly reduce simulation time. GNNR achieves up to 85% accuracy in predicting heat transfer coefficient.
Technical Paper

Design Optimization of Air Duct for Noise Reduction Using Gaussian Process Regression Algorithm

2024-10-17
2024-28-0042
In the context of Battery Electric Vehicles (BEVs), airborne noise from Heating, Ventilation and Air Conditioning (HVAC) ducts becomes a prominent concern in the view of passenger comfort. The automotive industry traditionally leverages Computational Fluid Dynamic (CFD) simulation to refine HVAC duct design and physical testing to validate acoustic performance. Optimization of the duct geometry using CFD simulation is a time-consuming process as various design configurations of the duct have to be studied for best acoustic performance. To address this issue effectively, the proposed a novel methodology uses Gaussian Process Regression (GPR) to minimize duct noise. Present solution demonstrates the power of machine learning (ML) algorithms in selecting the optimal duct configuration to minimize noise. Utilizing both real test data and CFD results, GPR achieves remarkable accuracy in design validation, especially for HVAC air ducts.
Technical Paper

Prediction of water film thickness due to condensation over instrument cluster based on Eulerian Wall Film approach of computational fluid dynamics

2024-10-17
2024-28-0009
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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