Application study on the dynamic programming algorithm for energy management of plug-in hybrid electric vehicles

Ximing Wang; Hongwen He; Fengchun Sun; Jieli Zhang

doi:10.3390/en8043225

Application study on the dynamic programming algorithm for energy management of plug-in hybrid electric vehicles

Ximing Wang, Hongwen He^*, Fengchun Sun, Jieli Zhang

^*Corresponding author for this work

School of Mechanical Engineering

Beijing Institute of Technology

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

161 Citations (Scopus)

Abstract

To explore the problems associated with applying dynamic programming (DP) in the energy management strategies of plug-in hybrid electric vehicles (PHEVs), a plug-in hybrid bus powertrain is introduced and its dynamic control model is constructed. The numerical issues, including the discretization resolution of the relevant variables and the boundary issue of their feasible regions, were considered when implementing DP to solve the optimal control problem of PHEVs. The tradeoff between the optimization accuracy when using the DP algorithm and the computational burden was systematically investigated. As a result of overcoming the numerical issues, the DP-based approach has the potential to improve the fuel-savings potential of PHEVs. The results from comparing the DP-based strategy and the traditional control strategy indicate that there is an approximately 20% improvement in fuel economy.

Original language	English
Pages (from-to)	3225-3244
Number of pages	20
Journal	Energies
Volume	8
Issue number	4
DOIs	https://doi.org/10.3390/en8043225
Publication status	Published - 2015

Keywords

Dynamic programming
Energy management strategy
Global optimization
Modeling
Plug-in hybrid electric vehicles

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.3390/en8043225

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abstract = "To explore the problems associated with applying dynamic programming (DP) in the energy management strategies of plug-in hybrid electric vehicles (PHEVs), a plug-in hybrid bus powertrain is introduced and its dynamic control model is constructed. The numerical issues, including the discretization resolution of the relevant variables and the boundary issue of their feasible regions, were considered when implementing DP to solve the optimal control problem of PHEVs. The tradeoff between the optimization accuracy when using the DP algorithm and the computational burden was systematically investigated. As a result of overcoming the numerical issues, the DP-based approach has the potential to improve the fuel-savings potential of PHEVs. The results from comparing the DP-based strategy and the traditional control strategy indicate that there is an approximately 20% improvement in fuel economy.",

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AU - Wang, Ximing

AU - He, Hongwen

AU - Sun, Fengchun

AU - Zhang, Jieli

PY - 2015

Y1 - 2015

N2 - To explore the problems associated with applying dynamic programming (DP) in the energy management strategies of plug-in hybrid electric vehicles (PHEVs), a plug-in hybrid bus powertrain is introduced and its dynamic control model is constructed. The numerical issues, including the discretization resolution of the relevant variables and the boundary issue of their feasible regions, were considered when implementing DP to solve the optimal control problem of PHEVs. The tradeoff between the optimization accuracy when using the DP algorithm and the computational burden was systematically investigated. As a result of overcoming the numerical issues, the DP-based approach has the potential to improve the fuel-savings potential of PHEVs. The results from comparing the DP-based strategy and the traditional control strategy indicate that there is an approximately 20% improvement in fuel economy.

AB - To explore the problems associated with applying dynamic programming (DP) in the energy management strategies of plug-in hybrid electric vehicles (PHEVs), a plug-in hybrid bus powertrain is introduced and its dynamic control model is constructed. The numerical issues, including the discretization resolution of the relevant variables and the boundary issue of their feasible regions, were considered when implementing DP to solve the optimal control problem of PHEVs. The tradeoff between the optimization accuracy when using the DP algorithm and the computational burden was systematically investigated. As a result of overcoming the numerical issues, the DP-based approach has the potential to improve the fuel-savings potential of PHEVs. The results from comparing the DP-based strategy and the traditional control strategy indicate that there is an approximately 20% improvement in fuel economy.

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KW - Energy management strategy

KW - Global optimization

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Application study on the dynamic programming algorithm for energy management of plug-in hybrid electric vehicles

Abstract

Keywords

UN SDGs

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