Maximizing power utilization of dual converter using predictive control with steady state cost

Abstract

Abstract Capability to deliver maximum power of a converter is essential for increasing power density that is limiting in many applications. Therefore, control algorithm should guarantee operation within converter thermal limits. This requirement can be formalized by a hard constraint in the cost function of model predictive control (MPC). However, the temperatures of the converter elements are not constant in the steady state, which complicates evaluation of the cost on long prediction horizon. Therefore, the evaluation is simplified utilizing the analysis of steady state behaviour of the model and derived current derating laws calculated in off‐line manner. The derating law is used as the terminal set in MPC which allows using one‐step‐ahead evaluation for efficient real‐time implementation. The steady state analysis also provides coefficients for power loss balancing. The proposed approach is applied to control of dual converter, which has high redundancy of switching elements and, thus, wide space for optimization. It is shown in simulation that the proposed approach has better performance than previously published algorithms, at lower computational cost. Experimental evaluation of the algorithm performed on a converter prototype of rated power of 10 kW shows that the proposed controller is able to safely operate the converter near the thermal limit.

Keywords

• Optimisation techniques
• Current control
• Power and energy control
• Control of electric power systems
• Optimisation techniques
• Power convertors and power supplies to apparatus