Experimental battery monitoring system design for electric vehicle applications

2018 IEEE International Conference on Industrial Electronics for Sustainable Energy Systems (IESES) Pub Date : 1900-01-01 DOI:10.1109/IESES.2018.8349847

S. M. Salamati, Cong-Sheng Huang, Bharat Balagopal, M. Chow

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引用次数: 8

Abstract

Li-ion batteries are considered as main energy sources for next generation of transportation systems. This paper presents a systematic way to design an efficient hardware testbed for Battery Monitoring System (BMS) applications in Electric Vehicle (EV) industry following the standard industrial communication protocol. The hardware testbed performs both the battery voltage/current data acquisition and the Co-Estimation algorithm. Co-Estimation is an electric circuit model based SOC estimation algorithm which takes model parameter variations into account. In this paper, the Co-Estimation algorithm is firstly discussed. A battery hardware testbed design is then elaborated, and reasons for selecting main components, including microcontroller and voltage/current sensors are explained. The performance of the hardware testbed is compared with MATLAB simulation result using the same Co-Estimation algorithm, showing similar performance between two different platforms: hardware testbed and software simulation.

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应用于电动汽车的实验性电池监测系统设计

锂离子电池被认为是下一代交通系统的主要能源。提出了一种基于标准工业通信协议的电动汽车电池监测系统(BMS)硬件测试平台的系统设计方法。硬件测试平台完成了电池电压/电流数据采集和协估计算法。协估计是一种考虑了模型参数变化的基于电路模型的SOC估计算法。本文首先讨论了协估计算法。然后阐述了电池硬件试验台的设计，并说明了主要组件的选择原因，包括单片机和电压/电流传感器。使用相同的协估计算法，将硬件试验台的性能与MATLAB仿真结果进行比较，在硬件试验台和软件仿真两个不同的平台上表现出相似的性能。

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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2018 IEEE International Conference on Industrial Electronics for Sustainable Energy Systems (IESES)

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