@ARTICLE{Wang_Shaohua_Research_2021, author={Wang, Shaohua and Zhang, Sheng and Shi, Dehua and Sun, Xiaoqiang and Yang, Tao}, volume={69}, number={3}, journal={Bulletin of the Polish Academy of Sciences Technical Sciences}, pages={e137064}, howpublished={online}, year={2021}, abstract={Due to the coexistence of continuity and discreteness, energy management of a multi-mode power split hybrid electric vehicle (HEV) can be considered a typical hybrid system. Therefore, the hybrid system theory is applied to investigate the optimum energy distribution strategy of a power split multi-mode HEV. In order to obtain a unified description of the continuous/discrete dynamics, including both the steady power distribution process and mode switching behaviors, mixed logical dynamical (MLD) modeling is adopted to build the control-oriented model. Moreover, linear piecewise affine (PWA) technology is applied to deal with nonlinear characteristics in MLD modeling. The MLD model is finally obtained through a high level modeling language, i.e. HYSDEL. Based on the MLD model, hybrid model predictive control (HMPC) strategy is proposed, where a mixed integer quadratic programming (MIQP) problem is constructed for optimum power distribution. Simulation studies under different driving cycles demonstrate that the proposed control strategy can have a superior control effect as compared with the rule-based control strategy.}, type={Article}, title={Research on hybrid modeling and predictive energy management for power split hybrid electric vehicle}, URL={http://www.czasopisma.pan.pl/Content/119663/PDF/10_01459_Bpast.No.69(3)_23.06.21_Druk.pdf}, doi={10.24425/bpasts.2021.137064}, keywords={power split HEV, energy management, mixed logical dynamical model, piecewise affine, model predictive control}, }