This paper presents a novel approach for tuning a proportional-integral-derivative (PID) controller applied to the active suspension system of an electric vehicle using the dingo optimization algorithm (DOA). The DOA is utilized as the core of a sophisticated controller tuning method and follows systematic rules to provide optimal gains to the PID, enhancing vehicle stability. As an outcome, the security and the comfort of the driver and passengers are increased, once the optimized controller can minimize the vehicle balance on irregular land. The active suspension model is based on a quarter-car representation. Three scenarios were considered in the simulation, including a flat road, a speed bump, and a road with a hole. The results demonstrate that the DOA-tuned PID controller effectively minimizes tracking errors, ensuring stable and precise control of the suspension system without excessive control effort. Another meta-heuristic approach was used for comparison, the Whale optimizer algorithm (WOA). The proposed controller presented superior performance, not developing the oscillatory behavior of the WOA-tuned algorithm. Moreover, the settling time using the proposed control approach is null. In this sense, the developed control system enhances the comfort and security of the driver and passengers.


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    Title :

    High-performance quarter car active suspension system using PID controller tuned by the dingo optimization algorithm




    Publication date :

    2024-10-20


    Size :

    556719 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English