Application Model of Quantum Sensing Technology in Battery Management System of New Energy Vehicles

This paper constructs an application model of quantum sensing technology in battery management system of new energy vehicles. It elaborates in detail the principle of quantum sensing technology using the high sensitivity of quantum state to small changes to achieve high-precision measurement of key parameters such as battery voltage, current, and state of charge (SOC). A battery SOC estimation algorithm based on quantum entangled state is proposed. With the help of the unique non-local correlation characteristics of quantum entangled state, the accuracy and stability of SOC estimation process are effectively improved. Through professional MATLAB/Simulink software, a battery management system simulation platform including accurate quantum sensor model is built, and comprehensive tests are carried out on mainstream new energy vehicle battery types in the market such as lithium iron phosphate and ternary lithium battery. The simulation data clearly shows that compared with the traditional SOC estimation algorithm, the new algorithm successfully reduces the SOC estimation error to within 1.5%, while the error of the traditional algorithm is usually maintained at about 5%; at the same time, the response time of battery pack balancing control is greatly shortened by 30%, which significantly improves the overall performance of BMS in all aspects, and provides a new idea with great potential for the innovation and development of new energy vehicle technology.