In this paper, a nonlinear model predictive RB (regenerative braking) controller for an IWMDEV (in-wheel-motors-driven electric vehicles) is proposed with considerations for improving the energy recovery and ensuring safety in low-TRFC (tire-road friction coefficient) cases. Simulations were conducted for two desired velocity profiles. They show that, by wisely distributing the braking torque to the front and rear wheels, the NMPC (nonlinear model predictive controller) is able to recover more RB energy than a conventional PI (proportional-integral) controller supplemented with FF (feedforward) control effort and another NMPC with no consideration of energy, especially for low-deceleration cases, without deterioration in the tracking performance. For the case where the RB efficiency characteristics are not identical for the front motors and the rear motors, the proposed NMPC can readily adjust the distribution pattern accordingly. Moreover, the safety during emergency braking on a low-friction road is also ensured by incorporating slip constraints into the NMPC formulation. A technique for achieving a better solution in the nonlinear optimization problem is also presented and shown to be effective.
Model predictive regenerative braking control for lightweight electric vehicles with in-wheel motors
2012
13 Seiten, 18 Bilder, 3 Tabellen, 26 Quellen
Article (Journal)
English
Personenkraftwagen , Elektroantrieb , Radnabenmotor , Nutzbremsung , modellprädiktive Regelung , Fahrzeugsicherheit , Reibung , Reifen (Fahrzeugreifen) , Straßenbelag , numerische Simulation , Geschwindigkeitsverteilung , Bremsmoment , Bremskraftverteilung , Energieeinsparung , Gefahrenbremsung , Bremsschlupf , nichtlineare Optimierung
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