## 1 Introduction
However, hybrid tractors do not meet the development trend of new energy vehicles for zero emissions. Moreover, the motors of hybrid tractors are mainly used as an auxiliary power source to improve the fuel efficiency of the engine, which cannot fully provide the characteristics of high efficiency and motor precision. Therefore, the DICPS was adopted to improve the overall efficiency of PETs. When the power demand is low, the PET can be driven by a single motor to increase the torque utilization factor of the motor. When the power demand is high, the PET can be driven by two motors to improve the operating efficiency of the DICPS. After the powertrain structure is determined, reasonable parameter sizing and control strategies are necessary to realize efficient operation of the dual-motor-driven electric tractor (DMET). However, the parameter-matching design method of a conventional tractor was not entirely suitable for DMET. For conventional tractors, only the dynamic performance indexes need to be satisfied, but the parameter matching of DICPSs should not only consider the dynamic indexes, but also the high-efficiency region distribution of the two motors [15; 16]. [PERSON] et al. proposed a method of powertrain parameter-matching and optimization design for a dual-motor-driven electric tractor, and used a particle swarm optimization algorithm based on a mixed penalty function to optimize the parameters [17]. The results showed that the selected optimization objectives had made evident progress after the optimization. However, they did not optimize the structure parameters according to the actual working condition data of the tractor. Therefore, it is necessary to study the matching optimization between the high-efficiency region of the two motors and the actual working conditions of the tractor. There have been some studies on control strategies for DICPSs. [PERSON] et al. proposed a real-time control strategy for a dual-input power-split transmission system [18]. The control strategy improved the overall efficiency of the vehicle at low speed and at frequent deceleration. However, the three PI controllers required a lot of debugging to obtain the best control parameters, a time-consuming process that was not able to guarantee robustness and timeliness. [PERSON] et al. used [PERSON]'s minimum principle (PMP) algorithm to optimize the control strategy of an electric bus driven by two motors under three driving cycles [19]. [PERSON] et al. proposed optimization-based energy management strategiesfor hybrid electric agricultural tractors to minimize fuel consumption in typical working cycles [20]. Compared with the typical rule-based strategy, these optimal energy management strategies (EMSs) showed significant improvements in fuel efficiency. Both PMP and Dynamic programming (DP) strategies require information of the entire cycle condition, and can only achieve global optimization under specific conditions. Computational complexity makes real-time operation difficult to achieve. The objectives of this study were to design a DICPS for a PET which could improve the PET's economic performance without compromising its dynamic performance. Furthermore, the system needs a reasonable parameter configuration and an effective energy management strategy to ensure the efficient operation of the PET. Furthermore, this study aimed to find the optimal parameter configuration for tractor working conditions through simulation experiments. The paper is organized as follows: Section 2.1 introduces the overall configuration of the DICPS. The modeling and driving modes of the DICPS are displayed in Section 2.2. The system parameters are matched and determined in Section 2.3. In Section 2.4, an EMS developed to minimize power loss and maximize overall system efficiency is explained. The simulation results and discussion are given in Section 3, where two typical working conditions were used to validate the effectiveness of the proposed method. Finally, conclusions are presented in Section 4.