Xiaoshuang Guo

To address the issue of over-regulation of the temperature of a liquid-cooled power battery thermal management system under the plowing condition of electric tractors, which leads to high energy consumption, a nonlinear model prediction control (NMPC) algorithm for the thermal management system of the power battery of electric tractors applicable to the plowing condition is proposed. Firstly, a control-oriented electric tractor power battery heat production model and a heat transfer model were established based on the tractor operating conditions and Bernardi’s theory of battery heat production. Secondly, in order to improve the accuracy of temperature prediction, a prediction method of future working condition information based on the moving average theory is proposed. Finally, a nonlinear model predictive control cooling optimization strategy is proposed, with the optimization objectives of quickly achieving battery temperature regulation and reducing compressor energy consumption. The proposed control strategy is validated by simulation and a hardware-in-the-loop (HIL) testbed. The results show that the proposed NMPC strategy can control the battery temperature better, that in the holding phase the proposed control strategy reduces the compressor speed variation range by 24.6% compared with PID, and that it reduces the compressor energy consumption by 23.1% in the whole temperature control phase.