Disturbance prediction-based enhanced stochastic model predictive control for hydrogen supply and circulating of vehicular fuel cells

•Enhanced stochastic MPC is proposed to regulate hydrogen excess ratio and pressure.•Markov exponential smoothing is applied and analyzed to forecast the vehicle speed.•By Markov process, the predicted vehicle speed-induced current is with stochastic.•Missing disturbance in the normal MPC can be filled by the stochastic prediction.•HIL results exhibited the prospect of the hydrogen MPC in the vehicular fuel cell. Hydrogen supply and circulating in vehicular fuel cells is crucial for their output capability and lifetime. In this article, an enhanced multiple-input multiple-output (MIMO) model predictive control (MPC) scheme is proposed for hydrogen regulation based on vehicle speed-induced fuel cell current disturbance stochastic prediction. The Markov exponential smoothing law is first developed for the vehicle speed prediction. The forecasted fuel cell power demand is obtained through vehicle dynamics model and rule-based energy management to release the predictive stack current regarding as the disturbance of hydrogen control system. The discrete predicted current sequence is with stochastic features and typed into the predictive model of MPC which is on longer the length of control horizon. Two case studies are presented to discuss the influence of different speed sampling times on the hydrogen regulation result under the proposed enhanced MPC. The enhanced MPC has a better performance than the traditional MPC, and the control RMSE of which can be reduced by 44.09% in case 1 and 69.78% in case 2 during automotive driving cycles. A dSPACE MicroAutoBox hardware in loop (HIL) experiment was conducted and the results well matched with the simulation which has verified the real-time performance of the enhanced MPC scheme.