Power loss minimization in electric cars by wheel force allocation
Licentiatavhandling, 2020

The need for lowering the emission levels has never been greater than now. In the vehicle industry, electrification seems to be an irreversible way ahead but user-related challenges such as limited range delay electricity as the primary energy source for personal transportation. Other control-related challenges are also introduced as electric cars are over-actuated, i.e. several actuators can be used for the same purpose. Over-actuation introduces the possibility to choose more freely which actuator to use when. Can this freedom of choice be used to improve energy efficiency of electric cars by e.g. minimizing power losses? In this thesis, two wheel force distribution algorithms have been developed with a method called control allocation. The algorithms minimize power losses in the electric drivetrain, transmission and tires. They were tested in a simulated city cycle in a Volvo V60 configuration with four electric motors, each connected to a wheel through a single speed transmission and coupling respectively. It was found that by using developed algorithms, up to 3.9% energy could be saved. In a next step, the transmission ratio on the front motors and rear motors were optimized in combination with one of the algorithms. By using a larger transmission ratio in the front than in the rear, the energy consumption reduced even further. With these development steps, up to 7.9% energy could be saved compared to the original vehicle.

control allocation

electric vehicles

energy efficiency

Online in Zoom (contact mats.jonasson@chalmers.se for password)
Opponent: Lars Drugge (KTH), Leo Laine (AB Volvo)


Juliette Torinsson

Chalmers, Mekanik och maritima vetenskaper, Fordonsteknik och autonoma system

Nästa generations algoritmer för att balansera energieffektivitet och fordonsdynamik för elbilar

Energimyndigheten, 2018-10-15 -- 2023-03-14.






Chalmers tekniska högskola

Online in Zoom (contact mats.jonasson@chalmers.se for password)


Opponent: Lars Drugge (KTH), Leo Laine (AB Volvo)

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