抄録
The paper presents the benchmark of control algorithm for flywheel energy storage system (FESS) with active magnetic bearing (AMB) on electric vehicle (EV). EV (especially, battery EV) cannot run long distance than gasoline vehicles. One of the solutions of this problem is using AMB FESS. If AMB FESS is useful for charger and discharger, EV can run long distance. But, because AMB FESS is unstable system, it must be controlled. Moreover, applying AMB FESS to EV, it will be complex system. So, it is necessary to benchmark controllers which are applied to AMB FESS on EV. Because of satisfying requirements of design which were given by motor companies, robust adaptive controllers were selected for AMB FESS controllers. The controllers were benchmarked by some evaluate items in simulation. The evaluate items are difficulty of design, disturbance suppression, and power consumption. Difficulty of design was quantitatively evaluated by the number of tuning parameters. Disturbance suppression was quantitatively evaluated by 2 norm and infinity norm of the displacement of flywheel rotor. Power consumption was quantitatively evaluated by the original function. Simulation was done on the assumption that normal driving by the flywheel-car (which was made by our group). Through the benchmark, interesting results and tendency are found. The most interesting result or tendency is that the controllers which have high rigidity and appropriate bias input can suppress power consumption of course disturbance. So, the first challengeable controller - Simple Adaptive Controller with epsilonl-modification and variable gamma approach (using bias control method) is proposed and verified the best robust adaptive control algorithm for AMB FESS on EV. The controller has high rigidity and appropriate bias input and can design easily. The controller has not so many tuning parameters.
