A predictive power management scheme for hybrid energy storage system in electric vehicle
Akhil Katnapally, Udaya Bhasker Manthati, Arunkumar Chirayarukil Raveendran, Srinivas Punna
Abstract
Abstract This paper presents a model predictive control (MPC) approach for energy management of a hybrid energy storage system (HESS), in an electric vehicle (EV). HESS constitutes the battery and the supercapacitor (SC) where the latter is used as an auxiliary source to reduce stress on the battery. Hence, an appropriate control strategy should be formulated for allocating low‐frequency power fluctuations to the battery and high‐frequency power fluctuations to SC. The conventional PI‐based control strategy has a difficult tuning process, and its performance is affected when the operating point fluctuates. Therefore, an MPC‐based control strategy is proposed because of its simplicity, intuitiveness, ease of implementation, and inclusion of nonlinearities and constraints. This paper provides a complete power management strategy for the HESS system, using a modified MPC approach which is simpler compared to the traditional MPC, for a multiple‐input bidirectional DC/DC converter. Firstly, the model of a dual input bidirectional DC/DC converter is developed, and a two‐loop control strategy is developed with predictive inner current control and outer voltage control for DC‐link voltage regulation and HESS energy management. Secondly, an SC voltage regulation loop is developed for enabling the charging and discharging of SC for reliable operation of the HESS system. Finally, simulation studies are done using MATLAB Simulink, and a prototype experimental setup is developed to validate the effectiveness of the proposed control strategy through the dSPACE platform.