Adaptive Model Predictive Control Including Battery Thermal Limitations for Fuel Consumption Reduction in P2 Hybrid Electric Vehicles
The primary objective of a hybrid electric vehicle (HEV) is to optimize the energy consumption of the automotive powertrain. This optimization has to be applied while respecting the operating conditions of the battery. Otherwise, there is a risk of compromising the battery life and thermal runaway t...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | World Electric Vehicle Journal |
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| Online Access: | https://www.mdpi.com/2032-6653/13/2/33 |
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| author | Ethelbert Ezemobi Gulnora Yakhshilikova Sanjarbek Ruzimov Luis Miguel Castellanos Andrea Tonoli |
| author_facet | Ethelbert Ezemobi Gulnora Yakhshilikova Sanjarbek Ruzimov Luis Miguel Castellanos Andrea Tonoli |
| author_sort | Ethelbert Ezemobi |
| collection | DOAJ |
| description | The primary objective of a hybrid electric vehicle (HEV) is to optimize the energy consumption of the automotive powertrain. This optimization has to be applied while respecting the operating conditions of the battery. Otherwise, there is a risk of compromising the battery life and thermal runaway that may result from excessive power transfer across the battery. Such considerations are critical if factoring in the low battery capacity and the passive battery cooling technology that is commonly associated with HEVs. The literature has proposed many solutions to HEV energy optimization. However, only a few of the solutions have addressed this optimization in the presence of thermal constraints. In this paper, a strategy for energy optimization in the presence of thermal constraints is developed for P2 HEVs based on battery sizing and the application of model predictive control (MPC) strategy. To analyse this approach, an electro-thermal battery pack model is integrated with an off-axis P2 HEV powertrain. The battery pack is properly sized to prevent thermal runaway while improving the energy consumption. The power splitting, thermal enhancement and energy optimization of the complex and nonlinear system are handled in this work with an adaptive MPC operated within a moving finite prediction horizon. The simulation results of the HEV SUV demonstrate that, by applying thermal constraints, energy consumption for a 0.9 kWh battery capacity can be reduced by 11.3% relative to the conventional vehicle. This corresponds to about a 1.5% energy increase when there is no thermal constraint. However, by increasing the battery capacity to 1.5 kWh (14s10p), it is possible to reduce the energy consumption by 15.7%. Additional benefits associated with the predictive capability of MPC are reported in terms of energy minimization and thermal improvement. |
| first_indexed | 2024-03-09T20:50:43Z |
| format | Article |
| id | doaj.art-81692c4ca740479db1e35416007f661e |
| institution | Directory Open Access Journal |
| issn | 2032-6653 |
| language | English |
| last_indexed | 2024-03-09T20:50:43Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | World Electric Vehicle Journal |
| spelling | doaj.art-81692c4ca740479db1e35416007f661e2023-11-23T22:35:51ZengMDPI AGWorld Electric Vehicle Journal2032-66532022-02-011323310.3390/wevj13020033Adaptive Model Predictive Control Including Battery Thermal Limitations for Fuel Consumption Reduction in P2 Hybrid Electric VehiclesEthelbert Ezemobi0Gulnora Yakhshilikova1Sanjarbek Ruzimov2Luis Miguel Castellanos3Andrea Tonoli4Department of Mechanical and Aerospace Engineering, Politecnico di Torino, 10129 Torino, ItalyDepartment of Mechanical and Aerospace Engineering, Politecnico di Torino, 10129 Torino, ItalyDepartment of Mechanical and Aerospace Engineering, Politecnico di Torino, 10129 Torino, ItalyDepartment of Mechanical and Aerospace Engineering, Politecnico di Torino, 10129 Torino, ItalyDepartment of Mechanical and Aerospace Engineering, Politecnico di Torino, 10129 Torino, ItalyThe primary objective of a hybrid electric vehicle (HEV) is to optimize the energy consumption of the automotive powertrain. This optimization has to be applied while respecting the operating conditions of the battery. Otherwise, there is a risk of compromising the battery life and thermal runaway that may result from excessive power transfer across the battery. Such considerations are critical if factoring in the low battery capacity and the passive battery cooling technology that is commonly associated with HEVs. The literature has proposed many solutions to HEV energy optimization. However, only a few of the solutions have addressed this optimization in the presence of thermal constraints. In this paper, a strategy for energy optimization in the presence of thermal constraints is developed for P2 HEVs based on battery sizing and the application of model predictive control (MPC) strategy. To analyse this approach, an electro-thermal battery pack model is integrated with an off-axis P2 HEV powertrain. The battery pack is properly sized to prevent thermal runaway while improving the energy consumption. The power splitting, thermal enhancement and energy optimization of the complex and nonlinear system are handled in this work with an adaptive MPC operated within a moving finite prediction horizon. The simulation results of the HEV SUV demonstrate that, by applying thermal constraints, energy consumption for a 0.9 kWh battery capacity can be reduced by 11.3% relative to the conventional vehicle. This corresponds to about a 1.5% energy increase when there is no thermal constraint. However, by increasing the battery capacity to 1.5 kWh (14s10p), it is possible to reduce the energy consumption by 15.7%. Additional benefits associated with the predictive capability of MPC are reported in terms of energy minimization and thermal improvement.https://www.mdpi.com/2032-6653/13/2/33energy minimizationadaptive model predictive controlbattery sizingthermal limitationmild hybrid electric vehicle |
| spellingShingle | Ethelbert Ezemobi Gulnora Yakhshilikova Sanjarbek Ruzimov Luis Miguel Castellanos Andrea Tonoli Adaptive Model Predictive Control Including Battery Thermal Limitations for Fuel Consumption Reduction in P2 Hybrid Electric Vehicles World Electric Vehicle Journal energy minimization adaptive model predictive control battery sizing thermal limitation mild hybrid electric vehicle |
| title | Adaptive Model Predictive Control Including Battery Thermal Limitations for Fuel Consumption Reduction in P2 Hybrid Electric Vehicles |
| title_full | Adaptive Model Predictive Control Including Battery Thermal Limitations for Fuel Consumption Reduction in P2 Hybrid Electric Vehicles |
| title_fullStr | Adaptive Model Predictive Control Including Battery Thermal Limitations for Fuel Consumption Reduction in P2 Hybrid Electric Vehicles |
| title_full_unstemmed | Adaptive Model Predictive Control Including Battery Thermal Limitations for Fuel Consumption Reduction in P2 Hybrid Electric Vehicles |
| title_short | Adaptive Model Predictive Control Including Battery Thermal Limitations for Fuel Consumption Reduction in P2 Hybrid Electric Vehicles |
| title_sort | adaptive model predictive control including battery thermal limitations for fuel consumption reduction in p2 hybrid electric vehicles |
| topic | energy minimization adaptive model predictive control battery sizing thermal limitation mild hybrid electric vehicle |
| url | https://www.mdpi.com/2032-6653/13/2/33 |
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