Real-time HEV energy management strategies

Qi Jiang (1) , Florence Ossart (1) , Claude Marchand (1)

1 GeePs - Laboratoire Génie électrique et électronique de Paris

Hybrid electric vehicles require an adequate energy management strategy in order to actually optimize their consumption. Many real-time controls were recently proposed in literature, but as each study is performed in a specific context, it is difficult to compare their efficiencies. The present paper proposes a comparison between 3 recent promising real-time strategies: adaptive equivalent consumption minimization strategy (A-ECMS), optimal control law (OCL) and stochastic dynamic programming (SDP). Two off-line methods are used as benchmark: Pontryagin's minimum principle (PMP) and dynamic programming (DP). They have the best performance in fuel saving while the other three are near-optimal strategies. Simulation results of a parallel HEV show 5% to 18% fuel economy, compared to a conventional vehicle.

Domaines: Sciences de l'ingénieur [physics]

Qi Jiang, Florence Ossart, Claude Marchand. Real-time HEV energy management strategies. 2nd Symposium de Génie Électrique (SGE 2016), Jun 2016, Grenoble, France. ⟨hal-01361674⟩