Digital twin modeling of a solar car based on the hybrid model method with data-driven and mechanistic

Solar cars are energy-sensitive and affected by many factors. In order to achieve optimal energy management of solar cars, it is necessary to comprehensively characterize the energy flow of vehicular components. To model these components which are hard to formulate, this study stim-ulates a solar car with the digital twin (DT) technology to accurately characterize energy. Based on the hybrid modeling approach combining mechanistic and data-driven technologies, the DT model of a solar car is established with a designed cloud platform server based on Transmission Control Protocol (TCP) to realize data interaction between physical and virtual entities. The DT model is further modified by the offline optimization data of drive motors, and the energy consumption is evaluated with the DT system in the real-world experiment. Specifically, the energy consumption error between the experiment and simulation is less than 5.17%, which suggests that the established DT model can accurately stimulate energy consumption. Generally, this study lays the foundation for subsequent performance optimization research.