Abstract
The Energy Management Strategy(EMS) of the Extended-Range Electric Bus (E-REB) plays an important role in the fuel economy and emission performance. This paper presents a Stochastic Model Predictive Control (SMPC) strategy based on Stochastic Dynamic Programming (SDP) and Model Predictive Control (MPC) for E-REB. SMPC applies Markov stochastic prediction model to predict the power demand of driving cycles, converts the SDP algorithm into the local optimization algorithm within the finite horizon, then the global suboptimal strategy can be obtained by solving a finite horizon optimization problem. SMPC can greatly save the online computation and operation time, achieve the goal of real-time online control. Simulation results of E-EVB are presented to demonstrate the effectiveness of the SMPC.
Original language | English |
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Pages (from-to) | 833-839 |
Number of pages | 7 |
Journal | Energy Procedia |
Volume | 88 |
DOIs | |
Publication status | Published - 1 Jun 2016 |
Event | Applied Energy Symposium and Summit on Low-Carbon Cities and Urban Energy Systems, CUE 2015 - Fuzhou, China Duration: 15 Nov 2015 → 17 Nov 2015 |
Keywords
- Energy Management Strategy(EMS)
- Extended-range electric bus (E-REB)
- Markov stochastic prediction model
- Stochastic Model Predictive Control (SMPC)