Optimization for the minimum fuel consumption problem of a hybrid electric vehicle using mixed-integer linear programming
In this study, a mixed-integer linear programming (MILP) formulation for obtaining the operating points of hybrid electric vehicle (HEV) powertrains is proposed. This study focuses on linearizing the nonlinear terms, such as an engine fuel consumption map, or bilinear terms represented by the energy...
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| Published in: | Engineering optimization Vol. 55; no. 9; pp. 1516 - 1534 |
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| Format: | Journal Article |
| Language: | English |
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Abingdon
Taylor & Francis
02.09.2023
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| ISSN: | 0305-215X, 1029-0273 |
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| Abstract | In this study, a mixed-integer linear programming (MILP) formulation for obtaining the operating points of hybrid electric vehicle (HEV) powertrains is proposed. This study focuses on linearizing the nonlinear terms, such as an engine fuel consumption map, or bilinear terms represented by the energy of the motor. To address this problem, a conventional piecewise linear (PWL) method and a multi-layer perceptron (MLP) regression approach are adopted. Although the optimal solution cannot be determined using a PWL approximation for the fuel consumption map, it can be obtained using an MLP regression. Furthermore, the PWL method achieves better results than the MLP approach in terms of the accuracy of its bilinear approximation. Obtaining the optimal solution using MILP helps in acquiring a Lagrange multiplication of the design variables by solving the dual problem, which allows an efficient design revision strategy to be obtained. |
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| AbstractList | In this study, a mixed-integer linear programming (MILP) formulation for obtaining the operating points of hybrid electric vehicle (HEV) powertrains is proposed. This study focuses on linearizing the nonlinear terms, such as an engine fuel consumption map, or bilinear terms represented by the energy of the motor. To address this problem, a conventional piecewise linear (PWL) method and a multi-layer perceptron (MLP) regression approach are adopted. Although the optimal solution cannot be determined using a PWL approximation for the fuel consumption map, it can be obtained using an MLP regression. Furthermore, the PWL method achieves better results than the MLP approach in terms of the accuracy of its bilinear approximation. Obtaining the optimal solution using MILP helps in acquiring a Lagrange multiplication of the design variables by solving the dual problem, which allows an efficient design revision strategy to be obtained. In this study, a mixed-integer linear programming (MILP) formulation for obtaining the operating points of hybrid electric vehicle (HEV) powertrains is proposed. This study focuses on linearizing the nonlinear terms, such as an engine fuel consumption map, or bilinear terms represented by the energy of the motor. To address this problem, a conventional piecewise linear (PWL) method and a multi-layer perceptron (MLP) regression approach are adopted. Although the optimal solution cannot be determined using a PWL approximation for the fuel consumption map, it can be obtained using an MLP regression. Furthermore, the PWL method achieves better results than the MLP approach in terms of the accuracy of its bilinear approximation. Obtaining the optimal solution using MILP helps in acquiring a Lagrange multiplication of the design variables by solving the dual problem, which allows an efficient design revision strategy to be obtained. |
| Author | Yamanaka, Gentaro Kuroishi, Masakatsu Matsumori, Tadayoshi |
| Author_xml | – sequence: 1 givenname: Gentaro orcidid: 0000-0002-5514-6467 surname: Yamanaka fullname: Yamanaka, Gentaro email: e1384@mosk.tytlabs.co.jp organization: Toyota Central R&D Labs. Inc – sequence: 2 givenname: Masakatsu surname: Kuroishi fullname: Kuroishi, Masakatsu organization: Toyota Central R&D Labs. Inc – sequence: 3 givenname: Tadayoshi orcidid: 0000-0001-9597-0285 surname: Matsumori fullname: Matsumori, Tadayoshi organization: Toyota Central R&D Labs. Inc |
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| SubjectTerms | Approximation Fuel consumption HEV hybrid electric vehicle powertrains Hybrid electric vehicles Integer programming Linear programming Mathematical analysis Mixed integer mixed-integer linear programming Multilayer perceptrons Multilayers operating point optimization Optimization Powertrain |
| Title | Optimization for the minimum fuel consumption problem of a hybrid electric vehicle using mixed-integer linear programming |
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