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Energy-Efficient Wheel Torque Distribution for Heavy Electric Vehicles with Adaptive Model Predictive Control and Control Allocation

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Název: Energy-Efficient Wheel Torque Distribution for Heavy Electric Vehicles with Adaptive Model Predictive Control and Control Allocation
Autoři: Janardhanan, Sachin, 1983, Persson, Jonas, Jonasson, Mats, 1969, Jacobson, Bengt, 1962, Gelso, Esteban, 1977, Henderson, L.
Zdroj: IEEE Open Journal of Vehicular Technology. 6:2909-2924
Témata: Electric vehicles, Model predictive control, Limit handling, Control allocation
Popis: This paper proposes an energy efficient hierarchical wheel torque controller for a 4×4 heavy electric vehicle equipped with multiple electric drivetrains. The controller consists of two main components: a global force reference generator and a control allocator. The global force reference generator computes motion requests based on steering wheel angle and longitudinal acceleration inputs, while adhering to actuator and tire force constraints. For this purpose, a linear time-varying model predictive controller (LTV-MPC) is employed to minimize the squared errors in yaw rate and longitudinal acceleration over a short prediction horizon. Concurrently, the controller dynamically identifies safe operating limits based on current driving conditions. These limits are then used to adjust the state cost weights dynamically, thereby improving the effectiveness of the MPC cost function. The control allocator (CA) subsequently distributes the force demands from the global reference generator among the electric machines and friction brakes. This allocation process minimizes instantaneous power losses while respecting actuator and tire force constraints. To further enhance energy efficiency, the method leverages the heterogeneous nature of the electric machines by minimizing not only operational power losses but also idle losses (power losses at zero torque), ensuring safe vehicle operation. The proposed strategy is evaluated using a high-fidelity vehicle model under various driving scenarios, including low-friction surfaces and near-handling-limit conditions. Simulation results demonstrate that dynamically varying state cost weights in conjunction with safe operating limits significantly improves vehicle performance, enhances energy efficiency, and reduces driver effort.
Popis souboru: electronic
Přístupová URL adresa: https://research.chalmers.se/publication/548854
https://research.chalmers.se/publication/548854/file/548854_Fulltext.pdf
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Items – Name: Title
  Label: Title
  Group: Ti
  Data: Energy-Efficient Wheel Torque Distribution for Heavy Electric Vehicles with Adaptive Model Predictive Control and Control Allocation
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Janardhanan%2C+Sachin%22">Janardhanan, Sachin</searchLink>, 1983<br /><searchLink fieldCode="AR" term="%22Persson%2C+Jonas%22">Persson, Jonas</searchLink><br /><searchLink fieldCode="AR" term="%22Jonasson%2C+Mats%22">Jonasson, Mats</searchLink>, 1969<br /><searchLink fieldCode="AR" term="%22Jacobson%2C+Bengt%22">Jacobson, Bengt</searchLink>, 1962<br /><searchLink fieldCode="AR" term="%22Gelso%2C+Esteban%22">Gelso, Esteban</searchLink>, 1977<br /><searchLink fieldCode="AR" term="%22Henderson%2C+L%2E%22">Henderson, L.</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <i>IEEE Open Journal of Vehicular Technology</i>. 6:2909-2924
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Electric+vehicles%22">Electric vehicles</searchLink><br /><searchLink fieldCode="DE" term="%22Model+predictive+control%22">Model predictive control</searchLink><br /><searchLink fieldCode="DE" term="%22Limit+handling%22">Limit handling</searchLink><br /><searchLink fieldCode="DE" term="%22Control+allocation%22">Control allocation</searchLink>
– Name: Abstract
  Label: Description
  Group: Ab
  Data: This paper proposes an energy efficient hierarchical wheel torque controller for a 4×4 heavy electric vehicle equipped with multiple electric drivetrains. The controller consists of two main components: a global force reference generator and a control allocator. The global force reference generator computes motion requests based on steering wheel angle and longitudinal acceleration inputs, while adhering to actuator and tire force constraints. For this purpose, a linear time-varying model predictive controller (LTV-MPC) is employed to minimize the squared errors in yaw rate and longitudinal acceleration over a short prediction horizon. Concurrently, the controller dynamically identifies safe operating limits based on current driving conditions. These limits are then used to adjust the state cost weights dynamically, thereby improving the effectiveness of the MPC cost function. The control allocator (CA) subsequently distributes the force demands from the global reference generator among the electric machines and friction brakes. This allocation process minimizes instantaneous power losses while respecting actuator and tire force constraints. To further enhance energy efficiency, the method leverages the heterogeneous nature of the electric machines by minimizing not only operational power losses but also idle losses (power losses at zero torque), ensuring safe vehicle operation. The proposed strategy is evaluated using a high-fidelity vehicle model under various driving scenarios, including low-friction surfaces and near-handling-limit conditions. Simulation results demonstrate that dynamically varying state cost weights in conjunction with safe operating limits significantly improves vehicle performance, enhances energy efficiency, and reduces driver effort.
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  Data: electronic
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1109/OJVT.2025.3619823
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 16
        StartPage: 2909
    Subjects:
      – SubjectFull: Electric vehicles
        Type: general
      – SubjectFull: Model predictive control
        Type: general
      – SubjectFull: Limit handling
        Type: general
      – SubjectFull: Control allocation
        Type: general
    Titles:
      – TitleFull: Energy-Efficient Wheel Torque Distribution for Heavy Electric Vehicles with Adaptive Model Predictive Control and Control Allocation
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            NameFull: Janardhanan, Sachin
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            NameFull: Persson, Jonas
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            NameFull: Gelso, Esteban
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            NameFull: Henderson, L.
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              M: 01
              Type: published
              Y: 2025
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              Value: 6
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            – TitleFull: IEEE Open Journal of Vehicular Technology
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