用于最优控制的电池充电状态和电压耦合模型

Masoomeh Karami, Sajad Shahsavari, E. Immonen, M. Haghbayan, J. Plosila
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引用次数: 1

摘要

对电动汽车(EV)电池进行优化控制,以实现最大的能效、安全性和寿命,这就要求电池管理系统(BMS)在任何时候都能准确掌握电池的充电状态(SoC)及其动态信息,即长期和短期的能量供应能力。然而,这些数量不能直接从电池中测量出来,而且,在实践中,通常只进行SoC估计。在本文中,我们提出了一种新的参数代数电压模型,该模型与著名的Manwell-McGowan动态动力电池模型(KiBaM)相耦合,能够预测电池SoC动态及其电响应。基于实验室测量,对柱状钛酸锂(LTO)电池进行了数值模拟。这种电池是现代重型越野电动汽车应用的主要候选者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Coupled Battery State-of-Charge and Voltage Model for Optimal Control Applications
Optimal control of electric vehicle (EV) batteries for maximal energy efficiency, safety and lifespan requires that the Battery Management System (BMS) has accurate real-time information on both the battery State-of-Charge (SoC) and its dynamics, i.e. long-term and short-term energy supply capacity, at all times. However, these quantities cannot be measured directly from the battery, and, in practice, only SoC estimation is typically carried out. In this article, we propose a novel parametric algebraic voltage model coupled to the well-known Manwell-McGowan dynamic Kinetic Battery Model (KiBaM), which is able to predict both battery SoC dynamics and its electrical response. Numerical simulations, based on laboratory measurements, are presented for prismatic Lithium-Titanate Oxide (LTO) battery cells. Such cells are prime candidates for modern heavy offroad EV applications.
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