An Adaptive Brake Force Allocation Strategy for Rear-Wheel Driven EVs

2026-01-0636

04/07/2025

Authors
Abstract
Content
Due to changed requirements compared to conventional propulsion concepts, electromobility demands new and innovative strategies for energy-efficient vehicle motion control. For example, the challenge in purely rear-wheel drive (RWD) electric vehicles (EVs) is to achieve a maximum of regenerative braking power in order to increase energy recovery and to ensure, that this does not impair the braking stability. Within this conflict between energy efficiency and braking dynamics, it is necessary to design an intelligent strategy to optimise recuperation. This paper presents such a strategy, which improves an existing approach formerly presented by the authors, but specifically optimises it to overcome weaknesses. The previous approach had two major limitations: First, the efficiency map of the in-wheel motors (IWMs) was not considered. Second, there was no possibility of switching flexibly between different brake force distributions to guarantee both, maximized recovery potential and high braking stability, in fulfilment of legislative requirements. The new strategy addresses these shortcomings by introducing a speed-dependent torque limit for the electric drive motors to avoid inefficient operating and uses two independent factors to manipulate the brake force distribution along the axles and vary the distribution between the actuators. In addition, various scenarios were analysed and incorporated into the new strategy in order to achieve optimal torque distribution in every driving situation. The developed approach was implemented into a real vehicle and extensively tested in driving trials on closed-off terrain and on public roads. The results of the investigation demonstrate the ability to ensure stable vehicle control and high energy recovery potential.
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Citation
Mitsching, Thomas, Marius Heydrich, and Valentin Ivanov, "An Adaptive Brake Force Allocation Strategy for Rear-Wheel Driven EVs," SAE Technical Paper 2026-01-0636, 2025-, .
Additional Details
Publisher
Published
Apr 7, 2025
Product Code
2026-01-0636
Content Type
Technical Paper
Language
English