Artificial Intelligence
Research on Intelligent Power Conditioning Method of Charger Based on Thermal Path Model
Fast charging technology plays a crucial role in advancing the development of electric vehicles. However, the operating environment of electric vehicles is complex, and internal temperatures can become extremely high under direct sunlight. If a vehicle charger operates at high power for extended periods, the internal power components may experience significant heat generation, potentially leading to failures. Therefore, it's essential for the charger to implement temperature control measures in high-temperature environments, reducing thermal stress on power devices and enhancing operational safety.
To address this challenge, researchers worldwide have begun exploring intelligent power control technologies [1]. These methods typically rely on real-time temperature monitoring of power components and adjust input power accordingly to improve device reliability. However, when a vehicle is driven on bumpy roads, it becomes difficult to directly measure the temperature rise of the power components, making traditional intelligent control methods less effective. In response, literature [2–3] proposed an unsteady-state measurement approach, where a thermal path model is established by analyzing transient temperature changes. While this method captures the dynamic temperature rise process, it does not fully account for the relationship between the device's operating current and ambient temperature, limiting its effectiveness in thermal protection.
To overcome these limitations, this paper proposes an intelligent power adjustment method based on a centralized parameter thermal path model of the power device. This approach eliminates the need for direct temperature measurement, instead using ambient temperature and input power to achieve thermal protection of the power components.
The principle of the intelligent power adjustment method involves identifying the worst-case power device in terms of temperature rise. Since direct temperature measurement is challenging, a thermal path model is built offline. The model helps establish a closed-loop control strategy that adjusts the charger’s input power based on temperature limits, ensuring safe operation.
The centralized parameter thermal path model simplifies the heat transfer process by considering the power device and heat sink as a single unit. Due to the relatively low thermal resistance of the power device compared to the heat sink, it can be neglected in the model. This allows for an accurate representation of steady-state temperature behavior, which is critical for thermal management.
Parameter estimation of the thermal path model is performed using a least-squares method. By collecting temperature and power data under various conditions, the model parameters are determined, enabling precise prediction of device temperatures.
An intelligent power adjustment strategy is then implemented, combining a power regulation outer loop with a current regulation inner loop. The outer loop calculates the maximum allowable temperature based on ambient conditions and adjusts the input power accordingly, while the inner loop ensures the output current remains within safe limits.
Experimental validation was conducted using a temperature rise test platform. Results showed that the MOSFET was the component most prone to overheating. Using the developed thermal model, the system effectively controlled the temperature, keeping it within safe limits even under high ambient temperatures. The proposed method significantly improved the reliability and safety of the charger under extreme conditions.
In conclusion, this study presents an effective intelligent power adjustment method tailored for vehicle chargers. By leveraging a centralized thermal path model and adaptive control strategies, the system ensures safe and efficient operation, even in high-temperature environments. Experimental results confirm the method’s effectiveness in maintaining device reliability and preventing thermal failure.
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