Motorcycle designers aim to enhance vehicle performance, stability, and safety, especially when the vehicle is approaching the tyres' friction limit. A strategy to achieve these purposes is to design All-Wheel Drive (AWD) vehicles with active torque distribution. Nowadays, effective technical solutions for powering the front wheel of a motorcycle have been proposed. The use of traction on both front and rear wheel is convenient when tyre friction is low, enhancing vehicle safety and performance. In this context, this paper presents a sensorless, open-loop traction strategy for AWD motorcycles that improves performance and stability both in straight running and in cornering, without requiring the knowledge of road-tyre adherence. This novel traction distribution strategy is based on the idea of maximising the area of the motorcycle performance envelope, also known as g-g diagram. A simplified mathematical model is used to find closed-form solution to this problem, then converted into a control algorithm for the front and rear driving torques. The performance of the proposed method is assessed with simulations: a detailed model of a light electric motorcycle is used for calculating the non-linear vehicle performance envelope, the acceleration response in straight running and cornering, and the response to road irregularities. Moreover, a comparison with feedback slip-based traction control system is conducted. Simulation results indicate that the AWD motorcycle outperforms the conventional rear wheel drive motorbike almost in all situations, especially when road-tyre adherence is low, and that no counter-indication for the adoption of the AWD architecture exists.


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    Title :

    A sensorless traction strategy for all-wheel drive electric motorcycles


    Contributors:

    Published in:

    Vehicle System Dynamics ; 60 , 11 ; 3668-3693


    Publication date :

    2022-11-02


    Size :

    26 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




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