A Single-Degree-of-Freedom Energy Optimization Strategy for Power-Split Hybrid Electric Vehicles
This paper presents a single-degree-of-freedom energy optimization strategy to solve the energy management problem existing in power-split hybrid electric vehicles (HEVs). The proposed strategy is based on a quadratic performance index, which is innovatively designed to simultaneously restrict the f...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-07-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/10/7/896 |
| _version_ | 1818005516290359296 |
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| author | Chaoying Xia Zhiming DU Cong Zhang |
| author_facet | Chaoying Xia Zhiming DU Cong Zhang |
| author_sort | Chaoying Xia |
| collection | DOAJ |
| description | This paper presents a single-degree-of-freedom energy optimization strategy to solve the energy management problem existing in power-split hybrid electric vehicles (HEVs). The proposed strategy is based on a quadratic performance index, which is innovatively designed to simultaneously restrict the fluctuation of battery state of charge (SOC) and reduce fuel consumption. An extended quadratic optimal control problem is formulated by approximating the fuel consumption rate as a quadratic polynomial of engine power. The approximated optimal control law is obtained by utilizing the solution properties of the Riccati equation and adjoint equation. It is easy to implement in real-time and the engineering significance is explained in details. In order to validate the effectiveness of the proposed strategy, the forward-facing vehicle simulation model is established based on the ADVISOR software (Version 2002, National Renewable Energy Laboratory, Golden, CO, USA). The simulation results show that there is only a little fuel consumption difference between the proposed strategy and the Pontryagin’s minimum principle (PMP)-based global optimal strategy, and the proposed strategy also exhibits good adaptability under different initial battery SOC, cargo mass and road slope conditions. |
| first_indexed | 2024-04-14T04:46:15Z |
| format | Article |
| id | doaj.art-21f19202ac9a496d8f5a78b2cf58157c |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-14T04:46:15Z |
| publishDate | 2017-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-21f19202ac9a496d8f5a78b2cf58157c2022-12-22T02:11:27ZengMDPI AGEnergies1996-10732017-07-0110789610.3390/en10070896en10070896A Single-Degree-of-Freedom Energy Optimization Strategy for Power-Split Hybrid Electric VehiclesChaoying Xia0Zhiming DU1Cong Zhang2School of Electrical and Information Engineering, Tianjin University, No. 92 Weijin Road, Tianjin 300072, ChinaSchool of Electrical and Information Engineering, Tianjin University, No. 92 Weijin Road, Tianjin 300072, ChinaSchool of Electrical and Information Engineering, Tianjin University, No. 92 Weijin Road, Tianjin 300072, ChinaThis paper presents a single-degree-of-freedom energy optimization strategy to solve the energy management problem existing in power-split hybrid electric vehicles (HEVs). The proposed strategy is based on a quadratic performance index, which is innovatively designed to simultaneously restrict the fluctuation of battery state of charge (SOC) and reduce fuel consumption. An extended quadratic optimal control problem is formulated by approximating the fuel consumption rate as a quadratic polynomial of engine power. The approximated optimal control law is obtained by utilizing the solution properties of the Riccati equation and adjoint equation. It is easy to implement in real-time and the engineering significance is explained in details. In order to validate the effectiveness of the proposed strategy, the forward-facing vehicle simulation model is established based on the ADVISOR software (Version 2002, National Renewable Energy Laboratory, Golden, CO, USA). The simulation results show that there is only a little fuel consumption difference between the proposed strategy and the Pontryagin’s minimum principle (PMP)-based global optimal strategy, and the proposed strategy also exhibits good adaptability under different initial battery SOC, cargo mass and road slope conditions.https://www.mdpi.com/1996-1073/10/7/896hybrid electric vehicleenergy management strategysimulation |
| spellingShingle | Chaoying Xia Zhiming DU Cong Zhang A Single-Degree-of-Freedom Energy Optimization Strategy for Power-Split Hybrid Electric Vehicles Energies hybrid electric vehicle energy management strategy simulation |
| title | A Single-Degree-of-Freedom Energy Optimization Strategy for Power-Split Hybrid Electric Vehicles |
| title_full | A Single-Degree-of-Freedom Energy Optimization Strategy for Power-Split Hybrid Electric Vehicles |
| title_fullStr | A Single-Degree-of-Freedom Energy Optimization Strategy for Power-Split Hybrid Electric Vehicles |
| title_full_unstemmed | A Single-Degree-of-Freedom Energy Optimization Strategy for Power-Split Hybrid Electric Vehicles |
| title_short | A Single-Degree-of-Freedom Energy Optimization Strategy for Power-Split Hybrid Electric Vehicles |
| title_sort | single degree of freedom energy optimization strategy for power split hybrid electric vehicles |
| topic | hybrid electric vehicle energy management strategy simulation |
| url | https://www.mdpi.com/1996-1073/10/7/896 |
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