Proton exchange membrane fuel cell (PEMFC)/battery hybrid electric vehicle is considered as promising transportation due to its eco-friendly characteristics. This article investigates a fuzzy logic (FL)-based adaptive backstepping sliding-mode control (BSMC) approach to generate stable charging current and voltage for battery charging applications on a non-plug-in PEMFC vehicle. An adaptive BSMC is proposed to address nonlinearities and disturbances caused by dc/dc buck converter, PEMFC, and equivalent load variations of batteries. Moreover, an FL-based approximation is utilized to estimate the time-varying equivalent load of batteries through the adaptive laws obtained by the defined Lyapunov function and can offer assistance estimating the state of charge (SOC) of batteries. Simulation comparisons between a proportional-integral (PI) control and the proposed FL-based adaptive BSMC were executed subsequently under certain conditions to validate the efficacy. Finally, experiments on the PEMFC/battery hybrid power system scaling prototype via NI (PCI-6229)-LabVIEW platform were implemented to test the charging performance of the proposed approach. The comparative results indicated that the FL-based adaptive BSMC method could regulate charging current and voltage against disturbance and uncertainty and estimate the equivalent load of batteries accurately.

中文翻译：

---

采用基于等效负载模糊逻辑估计的反步滑模控制进行抗干扰和抗不确定性的燃料电池车载充电电池


质子交换膜燃料电池（PEMFC）/电池混合动力电动汽车因其环保特性而被认为是一种有前途的交通运输方式。本文研究了一种基于模糊逻辑 (FL) 的自适应反步滑模控制 (BSMC) 方法，为非插入式 PEMFC 车辆上的电池充电应用生成稳定的充电电流和电压。提出了一种自适应 BSMC 来解决由 DC/DC 降压转换器、PEMFC 和电池等效负载变化引起的非线性和干扰。此外，基于FL的近似通过定义的Lyapunov函数获得的自适应定律来估计电池的时变等效负载，并且可以帮助估计电池的充电状态（SOC）。随后在某些条件下对比例积分（PI）控制和所提出的基于 FL 的自适应 BSMC 进行了仿真比较，以验证其功效。最后，通过NI (PCI-6229)-LabVIEW平台在PEMFC/电池混合电源系统扩展原型上进行实验，以测试所提方法的充电性能。对比结果表明，基于FL的自适应BSMC方法可以针对干扰和不确定性调节充电电流和电压，并准确估计电池的等效负载。