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首页> 外文期刊>Energy Conversion & Management >Implementation of an estimator-based adaptive sliding mode control strategy for a boost converter based battery/supercapacitor hybrid energy storage system in electric vehicles
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Implementation of an estimator-based adaptive sliding mode control strategy for a boost converter based battery/supercapacitor hybrid energy storage system in electric vehicles

机译:基于估计器的自适应滑模控制策略在电动汽车中基于升压转换器的电池/超级电容器混合储能系统的实现

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摘要

For the energy management of the boost converter based battery/supercapacitor (SC) hybrid energy storage system (HESS) in electric vehicles, a robust current control should be achieved for the battery such that the battery safety can be guaranteed. In this paper, an estimator-based adaptive sliding-mode control (estimator based ASMC) strategy is proposed for the current tracking control of the boost converter based battery/SC HESS. By considering the unmodeled dynamics of the SC and the unknown disturbances, the equivalent circuit and the state-space average model are established for the boost converter based battery/SC HESS. To achieve the current tracking control, a sliding surface is defined based on the estimated tracking current error. The average control factor is designed according to the sliding-mode control (SMC) strategy. Furthermore, the adaptation laws are designed based on the state observers and the Lyapunov function, which can be used to estimate the load variations and unknown external input voltage. Finally, the adaptive control factor is recalculated based on the estimator-based ASMC strategy. In practical application, a hysteresis control strategy and an average filter method are developed to guarantee the smooth SMC for the boost converter based battery/SC HESS. Simulations and experiments are established to verify the estimator-based ASMC strategy. Compared to the conventional total SMC (TSMC) and PI strategies, the estimator-based ASMC strategy has over 37% and 50% settling-time improvement of current adjustment to deal with the load variation, respectively. The estimator-based ASMC strategy can improve the operating stability of the boost converter based battery/SC HESS under different operating modes. The battery can provide a constant or optimal current to the load. Therefore, the boost converter based battery/SC HESS with the proposed estimator-based ASMC strategy can effectively ensure the system stability and extend the battery life, simultaneously.
机译:对于电动汽车中基于升压转换器的电池/超级电容器(SC)混合储能系统(HESS)的能量管理,应实现对电池的鲁棒电流控制,以确保电池安全。本文提出了一种基于估计器的自适应滑模控制(基于估计器的ASMC)策略,用于基于升压转换器的电池/ SC HESS的电流跟踪控制。通过考虑SC的未建模动力学和未知干扰,针对基于升压转换器的电池/ SC HESS建立了等效电路和状态空间平均模型。为了实现电流跟踪控制,基于估计的跟踪电流误差定义了一个滑动表面。平均控制因子是根据滑模控制(SMC)策略设计的。此外,基于状态观测器和Lyapunov函数设计了适应定律,这些函数可用于估计负载变化和未知的外部输入电压。最后,根据基于估计器的ASMC策略重新计算自适应控制因子。在实际应用中,开发了一种滞后控制策略和一种平均滤波方法,以确保基于升压转换器的电池/ SC HESS的平滑SMC。建立仿真和实验以验证基于估计的ASMC策略。与传统的总SMC(TSMC)和PI策略相比,基于估计器的ASMC策略分别将电流调整的建立时间提高了37%和50%,以应对负载变化。基于估计器的ASMC策略可以提高基于升压转换器的电池/ SC HESS在不同工作模式下的工作稳定性。电池可以为负载提供恒定或最佳的电流。因此,基于升压转换器的电池/ SC HESS与基于估计器的ASMC策略一起可以有效地确保系统稳定性并同时延长电池寿命。

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