An integrated control strategy of parallel-series hybrid electric powertrain systems for agricultural tractors

Nowadays, the electrification trend of agricultural tractors is obvious. For high-power tractors, the hybrid electric powertrain system is a good configuration at present. Due to the demands of continuous agricultural work, high-powered hybrid tractors depend more heavily on fuel than on high-voltage power batteries. This paper introduces an integrated control strategy for a series-parallel hybrid powertrain system to minimise the usage of high-voltage batteries. To reach this end, the control objective of the minimum DC bus current is selected to reduce the bus voltage fluctuation, slow down the high-voltage battery degradation, and decrease the cost of the high-voltage battery. Firstly, the powertrain model of the parallel-series hybrid electric tractor is established, whose components mainly include an engine, a generator, a motor, a battery, two clutches, and gear boxes. Based on this model, the energy conversion and dynamic parameters of the powertrain system can be described. Secondly, considering the different time scale characteristics of engine and generator/motor torque response, the powertrain control system is divided into two distinct subsystems named the fast control subsystem and the slow control system by using singular perturbation theory. Additionally, disturbance observers are incorporated to mitigate the influence of mechanical and electrical losses on control accuracy. Compared with the traditional thermostat control method and the optimal engine fuel consumption control strategy, experiments under ploughing conditions are conducted to validate the effectiveness of the proposed integrated control strategy. Concretely, the time-based variations in parameters including speed, torque, fuel efficiency, state of charge, and DC bus current are analyzed. The results demonstrate that the proposed control strategy for minimizing DC bus current can reduce battery usage to 6.93 % during the combined ploughing cycles.