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Stochastic DP Based on Trained Database for Sub-optimal Energy Management of Hybrid Electric Vehicles

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Informatics in Control, Automation and Robotics (ICINCO 2017)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 495))

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Abstract

This paper presents a sub-optimal energy management strategy, based on Stochastic Dynamic Programming (SDP), for efficient powersplit of a Hybrid Electric Vehicle (HEV). An optimal energy management strategy is proposed, permitting to have simultaneous speed profile and powersplit optimization of the HEV. Formulated as a multi-objective optimization problem, an \(\epsilon \)-constraint method has been used to find the Pareto front of the energy optimization task. Traffic conditions and driver behavior could be assimilated to a stochastic nature, thus, it is proposed in this paper to address the vehicle power as Markov Decision Process. A Stochastic Database is used to store Transition Probability and Reward Matrices, corresponding to suitable vehicle actions w.r.t. specific states. They are used afterwards to calculate sub-optimal powersplit policy for the vehicle via an infinite-horizon SDP approach. Simulation results demonstrate the effectiveness of the proposed approach compared to a deterministic strategy given in [1]. The present work is conducted on a dedicated high-fidelity model of the HEV that was developed on MATLAB/TruckMaker software.

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Notes

  1. 1.

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Authors and Affiliations

  1. Institut Pascal/IMobS3, UCA/SIGMA UMR CNRS 6602, Clermont-Ferrand, France

    Rustem Abdrakhmanov & Lounis Adouane

Authors
  1. Rustem Abdrakhmanov
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  2. Lounis Adouane
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Corresponding author

Correspondence to Rustem Abdrakhmanov .

Editor information

Editors and Affiliations

  1. Ford Research and Advanced Engineering, Dearborn, MI, USA

    Oleg Gusikhin

  2. University of Paris-EST Créteil (UPEC), Vitry sur Seine, France

    Kurosh Madani

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Abdrakhmanov, R., Adouane, L. (2020). Stochastic DP Based on Trained Database for Sub-optimal Energy Management of Hybrid Electric Vehicles. In: Gusikhin, O., Madani, K. (eds) Informatics in Control, Automation and Robotics . ICINCO 2017. Lecture Notes in Electrical Engineering, vol 495. Springer, Cham. https://doi.org/10.1007/978-3-030-11292-9_12

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