Nonlinear Model Predictive Control for power-split Hybrid Electric Vehicles

In this paper, the nonlinear model predictive control (NMPC) for the energy management of a power-split hybrid electric vehicle (HEV) has been studied to improve battery aging while maintaining the fuel economy at a reasonable level. A first principle battery model is built with simulation capacity of the battery aging features. The built battery model is integrated with an HEV model from autonomie software to investigate the vehicle and battery performance under control strategies. The NMPC has simplified battery models to predict the state of charge (SOC) change, the fuel consumption of the engine, and the battery aging index over the predicted horizon. The purpose of the NMPC is to find an optimized control sequence over the prediction horizon, which minimizes the designed cost function. The proposed control strategy is compared with that of an NMPC, which does not consider the battery aging. It is found that, with the optimized weighting factor selection, the NMPC with the consideration of battery aging has better battery aging performance and similar fuel economy performance comparing with the NMPC without the consideration of battery aging.

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Model Predictive Control Based Energy Management of Power-Split Hybrid Electric Vehicles in Presence of Uncertainty

Volume 2: Control and Optimization of Connected and Automated Ground Vehicles; Dynamic Systems and Control Education; Dynamics and Control of Renewable Energy Systems; Energy Harvesting; Energy Systems; Estimation and Identification; Intelligent Transportation and Vehicles; Manufacturing; Mechatronics; Modeling and Control of IC Engines and Aftertreatment Systems; Modeling and Control of IC Engines and Powertrain Systems; Modeling and Management of Power Systems ◽

10.1115/dscc2018-8961 ◽

2018 ◽

Cited By ~ 2

Author(s):

Baisravan HomChaudhuri ◽

Carrie M. Hall

Keyword(s):

Model Predictive Control ◽

Energy Management ◽

Predictive Control ◽

Electric Vehicles ◽

Constraint Satisfaction ◽

Hybrid Electric Vehicles ◽

Energy Management Strategy ◽

Terminal Set ◽

Power Split ◽

Hybrid Electric

A model predictive control (MPC) based robust energy management strategy for power-split hybrid electric vehicles (HEVs) is proposed in this paper which can guarantee charge sustaining constraint satisfaction in presence of uncertainty in future torque demand and vehicle velocity. The proposed method utilizes robust backward reachability analysis to pre-compute a robust set from where control solutions exist that ensure charge sustaining constraint satisfaction despite the uncertainty. This set is then used as the terminal set constraint of the MPC problem followed by tightening of state constraints for robust constraint satisfaction. An equivalent convex optimal control is then formulated which is solved in a receding horizon fashion. Simulation results show the efficacy of the proposed control strategy in robust constraint satisfaction.

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