MPC-based energy management system design for a series HEV with battery life optimization

Iman Shafikhani, Christofer Sundström, J. Åslund, E. Frisk
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引用次数: 2

Abstract

Simultaneous optimization of fuel consumption and battery lifetime is addressed in this work. A differential capacity degradation model is used to predict capacity loss, and linear time-varying and nonlinear MPC techniques are used to solve the energy management problem. It is shown that penalizing battery power in the MPC cost function can prolong battery lifetime by about 50 percent while achieving small gains in fuel economy compared to when the cost function only aims to minimize fuel consumption. An analysis of robustness against uncertainties in drive-cycle information shows that the controller is well-behaved and has good performance under uncertainty.
基于mpc的串联HEV电池寿命优化能量管理系统设计
同时优化燃料消耗和电池寿命在这项工作中得到解决。采用差分容量退化模型预测容量损失,采用线性时变和非线性MPC技术解决能量管理问题。研究表明,在MPC成本函数中惩罚电池电量可以延长电池寿命约50%,同时与成本函数仅以最小化燃料消耗为目标相比,在燃油经济性方面获得了小幅收益。对驱动循环信息不确定性的鲁棒性分析表明,该控制器在不确定性条件下具有良好的性能。
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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