Real-time implementation of an online Model Predictive Control for IPMSM using parallel computing on FPGA

Abstract

Model Predictive Control (MPC) offers a variety of advantages compared to conventional control methods. The problem with MPC is the high computational cost and the associated long control cycle time. This makes MPC unattractive for processes with small time constants, as in permanent magnet synchronous motors with interior magnets (IPMSM) for electric vehicles. In this paper a Model Predictive Control method for nonlinear systems with inherent output saturation is presented. This approach offers real-time capability for online MPC even for processes with time constants in the millisecond range. This becomes feasible by the possibility of parallel computation, as provided by a FPGA (Field Programmable Gate Array). This can overcome the drawbacks of the high computational effort. After the functional principle of this real-time MPC approach is presented, the resulting performance is shown by simulation results and the real-time capability is verified by test results of an IPMSM for automotive applications on a testbench.