Accurate estimation of the state of charge (SOC) and temperature of batteries is essential to ensure the safety of energy storage systems. However, it is very difficult to obtain multiple states of the battery with fewer sensors. In this paper, a joint estimation method for a lithium iron phosphate battery’s SOC and temperature based on ultrasonic reflection waves is proposed. A piezoelectric transducer is affixed to the surface of the battery for ultrasonic–electric transduction. Ultrasonic signals are excited at the transducer, transmitted through the battery, and transmitted back to the transducer by reaching the underside of the battery. Feature indicator extraction intervals of the battery state are determined by sliding–window matching correlation analysis. Virtual samples are used to expand the data after feature extraction. Finally, a backpropagation (BP) neural network model is applied to the multistate joint estimation of a battery in a wide temperature range. According to the experimental results, the root mean square error (RMSE) of the lithium-ion battery’s SOC and temperature estimation results is 7.42% and 0.40 °C, respectively. The method is nondestructive and easy to apply in battery management systems. Combined with the detection of gas production inside the battery, this method can improve the safety of the battery system.

Dynamic wireless charging technology can supply power for electric vehicle (EV) while it is in-motion. However, the system output stability is heavily influenced by the mutual inductance variation of the magnetic coupler, which is a major drawback of the EV dynamic wireless power transfer (EV-DWPT). This paper focuses on the primary coil design and its activating method. First, the LCC compensation network was adopted in both primary side and pick-up side of the system to achieve the constant primary current characteristic. Subsequently, a double-coil excitation method with the crossed-DD coil structure was proposed, which specifically concentrates on the feature of the dynamic mutual inductance. Simulation studies were carried out to prove the effectiveness of the proposed system. An EV-DWPT system prototype was performed to further verify the theoretical and simulation results.