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A Stochastic Model Predictive Control Approach for Hybrid Electric Vehicle Energy Management With Road Grade Preview

[+] Author Affiliations
Xiangrui Zeng, Junmin Wang

The Ohio State University, Columbus, OH

Paper No. DSCC2014-5998, pp. V002T20A001; 7 pages
  • ASME 2014 Dynamic Systems and Control Conference
  • Volume 2: Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization; Energy Storage, Optimization; Transportation and Grid Applications; Estimation and Identification Methods, Tracking, Detection, Alternative Propulsion Systems; Ground and Space Vehicle Dynamics; Intelligent Transportation Systems and Control; Energy Harvesting; Modeling and Control for Thermo-Fluid Applications, IC Engines, Manufacturing
  • San Antonio, Texas, USA, October 22–24, 2014
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-4619-3
  • Copyright © 2014 by ASME


Road grade preview can benefit the hybrid electric vehicle (HEV) energy management because the energy efficiency performance degrades significantly when the battery state of charge (SOC) reaches its boundaries and the road grade has a great influence on the battery SOC balance. In reality the road grade in front may be a random variable as the future route may not always be known to the vehicle controller. This paper proposes a stochastic model predictive control (MPC) approach which does not require a determined route known in advance. The road grade is modeled as a Markov chain and all the possible future routes are considered in building the transition matrix. A large-time-scale HEV energy consumption model is built. The HEV energy management problem is formulated as a finite-horizon Markov decision process and solved using stochastic dynamic programming (SDP). Simulation results show that the proposed approach can prevent the battery SOC from reaching its boundaries and maintain good fuel efficiency by the stochastic road grade preview.

Copyright © 2014 by ASME



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