Abstract Electric vehicles (EVs) are rapidly becoming a viable alternative to internal combustion engine vehicles (ICEVs). Despite the recent advances in battery technology, the driving range of an EV per charge is still shorter than that of an ICEV. The range of an EV can be increased by considering and factoring in all possible environmental information resulting in more energy efficient driving. A suitable way to reduce energy consumption can be devised by calculating an energy optimal speed profile and employing an advanced longitudinal control system to automatically track this speed profile. To this end, this chapter presents two model-based control approaches for longitudinal control of EVs that directly incorporate the most important design objectives, being tracking accuracy and ride comfort, in their control design: a novel exponentially stabilizing gain scheduling proportional-integral controller (gs-PI), and a state-of-the-art offset-free explicit model predictive controller with preview (e-MPC). These controllers were tested experimentally with an electric vehicle demonstrator on a 4 wheel drive rolling road for a realistic driving scenario. Comparison results are provided and show that both control approaches provide very promising behavior and achieve the prescribed performance criteria.


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    Title :

    Semi-autonomous Driving Based on Optimized Speed Profile




    Publication date :

    2017-01-01


    Size :

    19 pages




    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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