Load-current sensorless sliding-predictive control strategies for Boost converters
SHI Bingqing1, ZHAO Zhengming1, WEI Shusheng1, NIE Jintong1, LIN Yunzhi2
1. Department of Electrical Engineering, Tsinghua University, Beijing 100084, China; 2. China Railway Electrification Bureau Group Co., Ltd, Beijing 100071, China
Abstract：Boost converters are widely used for photovoltaic power generation, energy storage and electric vehicles. However, since the right half plane of the Boost converter is zero in the frequency domain, traditional PI control algorithms for the converter have serious dynamic response limitations which can result in large output voltage fluctuations leading to over or under voltage faults during fast transitions with large load changes. Predictive control can improve the dynamic response and avoid control parameter tuning with additive system constraints, but predictive control can lead to output voltage errors at steady state. A load-current sensorless sliding-mode-predictive control algorithm was developed here to reduce the output voltage fluctuations during sudden load transitions while also maintaining the proper steady-state characteristics. The outer loop uses a sliding surface to generate the inductor current reference while the inner loop with a deadbeat predictive control regulates the inductor current. The load current is estimated by a sliding mode observer. This control algorithm reduces the output voltage fluctuations during load transitions and the transition times. The algorithm also limits the output voltage errors at steady state. In addition, the algorithm does not require a load current sensor. Tests with a Boost converter confirm the effectiveness of this control strategy.
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2019, Vol. 59 
