Thermal runaway spreading prediction method, and thermal runaway spreading prediction system

Abstract

The invention discloses a thermal runaway spreading prediction method, and a thermal runaway spreading prediction system. The prediction method comprises the following steps: a maximum temperature rise rate value, working temperature, and maximum surface temperature are preset in a control device; the control device receives battery surface temperature fed back by a second temperature sensor; the control device receives environment temperature fed back by a first temperature sensor and a thermodynamic cloud picture fed back by a thermal imager; the control device obtains a real-time voltage value, a real-time current value, and a real-time charge state of a battery pack; the control device obtains a predicted temperature value according to the environment temperature, the thermodynamic cloud picture, the battery surface temperature, the real-time voltage value, the real-time current value, and the real-time charge state; the control device calculates a temperature rise rate according to the predicted temperature value; when the temperature rise rate is greater than a preset maximum value of the temperature rise rate, the control device outputs a control instruction with a thermal runaway problem. According to the prediction method disclosed by the invention, quantitative prediction of the thermal runaway spreading condition can be realized, the safety of lithium batteries during working is improved, and accidents are avoided.

Description

technical field [0001] The invention relates to the technical field of battery safety, in particular to a method and system for predicting thermal runaway spread. Background technique [0002] Thermal runaway of lithium-ion batteries is a key issue restricting the industrialization of the electric vehicle industry; thermal runaway of lithium batteries may occur under extreme working conditions, and thermal runaway of single batteries may lead to thermal spread, which will lead to thermal runaway of the module where the battery is located , battery box and even the safety of the whole vehicle, so it is necessary to study and evaluate the heat spread caused by thermal runaway. [0003] The existing thermal runaway prediction methods are generally based on experiments or models, but both prediction methods have the problem of large errors in prediction results, and cannot quantitatively estimate the thermal runaway spread of lithium batteries. [0004] It can be seen that the ...

AI Technical Summary

Problems solved by technology

[0003] The existing thermal runaway prediction methods are generally based on experiments or models, but both prediction methods have the problem of large prediction results errors, and cannot quantitatively estimate the thermal runaway spread of lithium batteries

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