Fast and Global Optimal Energy-Efficient Control Allocation With Applications to Over-Actuated Electric Ground Vehicles


This paper presents a fast and world optimization algorithm for an energy-efficient control allocation (CA) scheme, that was proposed for improving the operational energy efficiency of over-actuated systems. For a class of realistic actuator power and potency functions, a Karush-Kuhn-Tucker (KKT)-primarily based algorithm was devised to seek out all the native optimal solutions, and consequently the global minimum through a more simple comparison among all the realistic native minima and boundary values for such a non-convex optimization downside. This KKT-based mostly algorithm is also independent on the picks of initial conditions by transferring the quality nonlinear optimization problem into classical eigenvalue issues. Numerical examples for electric vehicles with in-wheel motors were used to validate the effectiveness of the proposed international optimization algorithm. Simulation results, based on the parameters of an electric ground vehicle actuated by in-wheel motors (whose energy efficiencies were experimentally calibrated), showed that the proposed international optimization algorithm was a minimum of twenty times faster than the classical active-set optimization method, whereas achieving better control allocation results for system energy saving.

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