Abstract
The paper is devoted to intelligent control of road electric vehicles, aiming at reducing energy losses at braking in traffic jams, changing velocity, and frequent start-stop modes of driving. A proposed gradient control method provides fuzzy adjustment and stabilisation of the braking torque with its allocation between electric and friction brakes, which allows integrating the advantages of both friction and electric braking. In the offered system, multiple factors are addressed, such as air resistance, road slope, and variable friction. Detailed motor and energy source models reflect the state of charge and electric current/voltage restrictions of the hybrid energy storage. Various driving scenarios are recognised, including gradual deceleration and emergency stop. Using the designed fuzzy logic and fuzzy PID controllers, consistently high braking quality can be realised, regardless of the road surface and slope uncertainty, vehicle initial velocity, and air resistance. The best results are obtained by connecting a master fuzzy logic controller with a slave PID controller. This kind of the intelligent controller successfully adjusts and stabilises the requested braking torque without overshoot, within a short settling time.
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This work was supported by the Estonian Research Council grant PRG 658.
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Vodovozov, V., Petlenkov, E., Aksjonov, A., Raud, Z. (2022). Simulation Study of Electric Vehicles at Fuzzy PID Control of Braking Torque. In: Gusikhin, O., Madani, K., Zaytoon, J. (eds) Informatics in Control, Automation and Robotics. ICINCO 2020. Lecture Notes in Electrical Engineering, vol 793. Springer, Cham. https://doi.org/10.1007/978-3-030-92442-3_15
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