u003cpu003e Abstract: According to the different parameters such as the number of batteries and battery capacity used by different models, a lithium battery pack
management system is designed. The system is based on single-chip microcomputer and CAN bus communication. It uses a distributed network control system structure to detect various operating parameters of the battery in real time; performs battery balancing, fault diagnosis and alarm according to the battery status; system parameter calibration through man-machine interface; Read historical storage information for offline analysis, improve SOC estimation methods and reduce failure analysis costs. The test results show that the system runs stably and reliably, and can be applied to different vehicle models. The voltage measurement accuracy is ±5mV, and the SOC accuracy is 7%.u003c/pu003eu003cpu003e As the main energy storage element in electric vehicles, batteries are the main components of electric vehicles. The key components directly affect the performance of electric vehicles. Lithium iron phosphate power battery has become the mainstream power source for new energy vehicles with its superior battery performance. As the most critical core component of new energy vehicles, the charge and discharge performance, service life and reliability of lithium-ion power batteries will directly affect the cost and performance of the vehicle. In order to extend the service life of the battery, reduce the cost of use, and ensure its safety and reliability, this paper designs a lithium battery pack
management system to realize online detection, fault diagnosis and alarm, control and offline analysis of the power battery. The main purpose of the battery management system is to detect the voltage, current and temperature of the battery in real time; to estimate the state of charge of the battery, that is, SOC (state ofu003c/pu003eu003cpu003echarge); to balance the inconsistency between the single cells ; Realize the communication between various modules; analyze the historical storage information offline; apply to different types of electric vehicles. The main research content framework is as follows: 1 hardware design 1.1 design of voltage and temperature acquisition module 1.2 equalization circuit 1.3 fault diagnosis and alarm 1.4 anti-interference design 2 software design 2.1 SOC estimation 2.2 CAN bus and storage module 2.3 parameter calibration program 3 system testu003c/p u003eu003c/pu003e
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