Model Based Analysis and Multi-objective Optimization of an Electric Pickup truck for Range, Acceleration, Drivability, Handling and Ride Comfort Performances

2021 IEEE Transportation Electrification Conference (ITEC-India) Pub Date : 2021-12-16 DOI:10.1109/ITEC-India53713.2021.9932452

Elavarasan Dharumaseelan, A. Karandikar, Rajavignesh Srinivasan, Sandeep Rapol, Anand Pichaikani

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Abstract

Today's electric vehicles are complex multi-domain systems catering for many customer and legal objectives that are often exclusive among each other. Finding optimal vehicle design configuration is the key in trade off among these objectives. These challenges require integrated design and optimization using model based systems engineering approach from the start of the development. In this paper, model based analysis and multi-objective optimization is done for an electric pickup truck to improve range, acceleration, drivability, handling and ride comfort performances of the vehicle. Detailed model of the electric pickup truck is created in a Modelica platform using multi-body and multi-domain approach. Functional mock-up unit (FMU) created from the model is used to run DoE, Optimization and Trade space analysis using an optimization tool. Finally, the optimized vehicle design configuration is presented that produces best trade off among the given objectives.

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基于模型的电动皮卡续航里程、加速性能、驾驶性能、操控性和平顺性多目标优化

今天的电动汽车是一个复杂的多领域系统，要满足许多客户和法律目标，而这些目标往往是相互排斥的。寻找最佳的车辆设计配置是权衡这些目标的关键。这些挑战需要从开发开始就使用基于模型的系统工程方法进行集成设计和优化。为提高电动皮卡的续航里程、加速性能、驾驶性能、操纵性能和乘坐舒适性，对电动皮卡进行了基于模型的分析和多目标优化。采用多体多域方法，在Modelica平台上建立了电动皮卡的详细模型。从模型中创建的功能模型单元(FMU)用于使用优化工具运行DoE，优化和贸易空间分析。最后，给出了在给定目标之间产生最佳折衷的优化车辆设计构型。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2021 IEEE Transportation Electrification Conference (ITEC-India)

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