<div class="csl-bib-body">
<div class="csl-entry">Klein, D., Mandl, P., Plöchl, M., Klinger, F., & Edelmann, J. (2026). Power optimal torque distribution for overactuated electric vehicles: analysis and experimental validation. <i>Automotive and Engine Technology</i>, <i>11</i>(1). https://doi.org/10.1007/s41104-025-00164-8</div>
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dc.identifier.issn
2365-5127
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/224160
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dc.description.abstract
The optimal integration of redundant actuators in an overactuated vehicle may be found by considering energy efficiency in the actuator allocation strategy. This paper investigates the potential to reduce the drive power demand of an electric vehicle with wheel individual drive through optimal allocation of drive torques and steering angles at the front and rear wheels. The actuator allocation problem is considered for the entire feasible normal and tangential acceleration range of the vehicle. The influences of electrical power losses of the motor-inverter system and tyre slip power losses on power demand are examined. By just considering the tyre slip power losses, the optimal control allocation reduces the drive power demand up to 20%, with the most significant reduction in the region of medium to high normal and tangential accelerations. The potential power reduction with respect to suboptimal strategies is validated in simulation and experimental tests by implementing the optimal torque distribution strategy as a feed-forward control on a demonstrator vehicle. The theoretically found power reduction gains are experimentally validated.
en
dc.language.iso
en
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dc.publisher
Springer Nature
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dc.relation.ispartof
Automotive and Engine Technology
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dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
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dc.subject
Energy efficiency
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dc.subject
Mechanical power optimal drive torque distribution
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dc.subject
Torque vectoring
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dc.subject
Wheel individual electric drive
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dc.subject
Rear wheel steering
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dc.title
Power optimal torque distribution for overactuated electric vehicles: analysis and experimental validation