# A Novel Optimal Control Strategy of Four Drive Motors for an Electric Vehicle
## 1 Introduction  
The benefits of replacing petroleum fuel with electric power include environmental, economic, and energy security aspects [1]. Electric power can be generated from renewable sources, such as solar, wind, and hydropower, which can significantly reduce carbon emissions and help mitigate climate change issues [2]. Using electric power instead of petroleum can reduce the emission of nitrogen oxides, sulfur oxides, and particulates [3]. Equipment powered by electricity typically has lower operating costs than those driven by petroleum fuels due to their more stable electricity prices and less maintenance required [4]. Electricity can be produced from various sources, including nuclear, renewable energy,and fossil fuels, and this diversity reduces the risk of disruption in single-source energy supply [5]. Vehicles that currently use electric power as their primary energy source include pure electric cars, fuel cell vehicles, etc. Electric vehicles use motors with high energy conversion efficiency as their power source, have no exhaust emissions, and are generally considered the optimal mode of transportation in all sectors. However, they have disadvantages, such as low range and inconvenient charging [6]. The significant increase in various types of electric vehicles has led to the emergence of multiple electric vehicle structures, electric vehicle charging infrastructure, electric vehicles based on renewable energy, and integrated electric vehicle systems with the grid. To effectively manage the charging process, unique control strategies and power management strategies need to be implemented for multi-source electric vehicle systems [7]. However, the use of electric vehicles has some disadvantages, such as a limited battery range, a relatively short battery life, and a lack of existing electric vehicle charging infrastructure [8]. Based on previous studies, the optimization of hybrid energy/power systems primarily aims at energy conservation and cost reduction to achieve higher overall efficiency and enhance the overall system's power [9]. Therefore, energy management strategies and the design of electric/power systems are two primary considerations. To obtain the optimal energy management strategy, rule-based control (RBC) is widely used in hybrid power systems [10]. This method is characterized by its ease of implementation, high computational efficiency, and rapid experimental verification. However, it inherently has the drawbacks of complex or highly nonlinear systems, limited to engineering intuitive design. To address such issues and enhance robustness, given the system's uncertainties, fuzzy logic control (FLC) is suitable for various types of hybrid power systems [11; 12]. The optimization can be carried out in parallel hybrid vehicles using dynamic programming algorithms and by designing driving cycles to determine the optimal hybridization factor and evaluate parameter sensitivity [13]. Dynamic programming has been widely referenced in numerous studies on hybrid vehicles and aircraft. It can determine the optimal trajectory by backtracking along the relationship between global power demand and time [14]. However, in systems with many control variables, a large number of logic rules may be required. Rule-based control can easily integrate global search results and verify controls with system variables. To overcome the quantitative analysis disadvantages derived from rule-based control, the concept of equivalent consumption minimization strategies (ECMS) is used to search for the best control (electric/power) source globally [15]. The ECMS requires dynamic calculations based on real-time data, which introduces significant computational complexity, increases the load on the controller, and demands higher hardware specifications. Under conditions of high-frequency operational changes, this computational load becomes particularly evident [16].