Control Strategy for an Electromechanical Transmission Vehicle Based on a Double Markov Process

Hui Liu; Riming Xu; Lijin Han; Shanshan Xiong

doi:10.1007/s12239-021-0069-4

Control Strategy for an Electromechanical Transmission Vehicle Based on a Double Markov Process

Hui Liu, Riming Xu, Lijin Han^*, Shanshan Xiong

^*Corresponding author for this work

School of Mechanical Engineering

Beijing Institute of Technology

Research output: Contribution to journal › Article › peer-review

4 Citations (Scopus)

Abstract

Based on an analysis of the driving demand and system dynamics of heavy-duty vehicles equipped with electromechanical transmission (EMT), a double Markov model is put forward to represent drivers’ power demand for driving and electricity. Transfer probability matrices are calculated by utilizing the maximum likelihood estimation method. A power distribution control strategy based on stochastic dynamic programming (SDP) is proposed. With economy being the optimization goal, the model for power allocation control based on SDP is established while regarding the engine torque, motor speeds, vehicle speed and state of charge (SOC) as state variables’ engine speed and motor torques as control variables’ and power demands as interference variables. The SDP problem is solved by an improved policy iteration algorithm based on value iteration and policy iteration algorithms.

Original language	English
Pages (from-to)	761-770
Number of pages	10
Journal	International Journal of Automotive Technology
Volume	22
Issue number	3
DOIs	https://doi.org/10.1007/s12239-021-0069-4
Publication status	Published - Jun 2021

Keywords

Control strategy
Double Markov model
Electro-mechanical transmission
Stochastic dynamic programming

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10.1007/s12239-021-0069-4

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title = "Control Strategy for an Electromechanical Transmission Vehicle Based on a Double Markov Process",

abstract = "Based on an analysis of the driving demand and system dynamics of heavy-duty vehicles equipped with electromechanical transmission (EMT), a double Markov model is put forward to represent drivers{\textquoteright} power demand for driving and electricity. Transfer probability matrices are calculated by utilizing the maximum likelihood estimation method. A power distribution control strategy based on stochastic dynamic programming (SDP) is proposed. With economy being the optimization goal, the model for power allocation control based on SDP is established while regarding the engine torque, motor speeds, vehicle speed and state of charge (SOC) as state variables{\textquoteright} engine speed and motor torques as control variables{\textquoteright} and power demands as interference variables. The SDP problem is solved by an improved policy iteration algorithm based on value iteration and policy iteration algorithms.",

keywords = "Control strategy, Double Markov model, Electro-mechanical transmission, Stochastic dynamic programming",

author = "Hui Liu and Riming Xu and Lijin Han and Shanshan Xiong",

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AU - Liu, Hui

AU - Xu, Riming

AU - Han, Lijin

AU - Xiong, Shanshan

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AB - Based on an analysis of the driving demand and system dynamics of heavy-duty vehicles equipped with electromechanical transmission (EMT), a double Markov model is put forward to represent drivers’ power demand for driving and electricity. Transfer probability matrices are calculated by utilizing the maximum likelihood estimation method. A power distribution control strategy based on stochastic dynamic programming (SDP) is proposed. With economy being the optimization goal, the model for power allocation control based on SDP is established while regarding the engine torque, motor speeds, vehicle speed and state of charge (SOC) as state variables’ engine speed and motor torques as control variables’ and power demands as interference variables. The SDP problem is solved by an improved policy iteration algorithm based on value iteration and policy iteration algorithms.

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Control Strategy for an Electromechanical Transmission Vehicle Based on a Double Markov Process

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Keywords

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