使用 xDomain 车辆仿真进行电动汽车高压电池健康预测

Aurobbindo Lingegowda, Dibakar Mahalanabish, Martin Johannaber
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引用次数: 0

摘要

车辆系统由不同领域的子系统(如制动、转向、热等)、组件、元件以及与其相互作用的环境因素组成。车辆的使用或任务特性会影响负载如何从车轮传递到相应的动力总成组件,从而产生能量。在当今先进的电气化、互联和自动驾驶汽车系统中,跨领域的整体互动耦合非常紧密,对其进行详细分析非常繁琐。xDomain 仿真可实现这一目的,它由多物理场车辆模型组成,能够代表复杂的车辆系统架构及其交互子系统和组件,用于在多种测试条件下进行各种系统分析。在这项工作中,根据 24 小时的真实驾驶信息,建立了一个包含所有与能量流相关元素的电动汽车模型和虚拟道路。高压电池的运行情况会计算出相关数量,这些数量将用于详细的高压电池模型,以进行关键的电池健康预测/估算。 关键词: xDomain 仿真 电动汽车 电池健康 电池电压 高压电池
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Use of xDomain Vehicle Simulation for Electric Vehicle HV Battery Health Prediction
A vehicle system comprises of various domain subsystems (e.g., Brakes, Steering, Thermal etc.,) components, elements, and the environmental factors with which it interacts. The vehicle usage or mission characteristics influence how the load are transferred from wheels to corresponding powertrain components which deliver energy. In today’s advanced electrified, connected & automated vehicle systems, the overall cross-domain interactions are very tightly coupled, and their detailed analysis is cumbersome. To predict component performance/Degradation over the life cycle it is necessary to estimate the real load conditions and the virtual environment is a key enabler. xDomain simulation serves this purpose which comprises multi-physics vehicle models capable of representing complex vehicle system architectures along with its interacting subsystems & components used for various system analysis under many test conditions. In this work, an Electric Vehicle model with all the elements relevant to Energy flow has been built along with the virtual road based on real driving information for 24 hours duration. High Voltage Battery operations are calculated for Quantity of Interest which would be used in a detailed HV Battery model for critical Battery health Prediction/Estimating. Keywords: xDomain, Simulation, Electric Vehicle, battery health, battery voltage, HV battery
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