XGBoost-Based Error Compensation Method for Acoustic Source Localization of Lithium-Ion Battery Thermal Runaway

An XGBoost-based lithium-ion battery thermal runaway acoustic source localization error compensation method, characterized by specifically comprising following steps:

• step S1:
• building and training a battery thermal runaway acoustic source localization error compensation system
• step S1.1:
• building a lithium-ion battery thermal runaway acoustic source localization error compensation system;
• the system comprising an energy storage cabin for placing a lithium-ion battery, an acoustic acquisition assembly installed in the energy storage cabin, and a controller provided at a remote end, wherein the controller comprises an acoustic signal recognition model and an XGBoost model training module;
• step S1.2:
• acquiring training data:
• specifically comprising following steps:
• step S1.2.1:
• pre-collecting areal lithium-ion battery safety valve opening audio and storing the audio in an audio player;
• step S1.2.2:
• placing an audio player in the position of the lithium-ion battery in the energy storage cabin in step S1, and playing the audio, simulating a position of the real lithium-ion battery safety valve opening acoustic source, and using an acoustic acquisition assembly to acquire the audio signal for each playback;
• step S1.2.3:
• performing the operations of step S1.2.2 on each position where the lithium-ion battery is placed in the energy storage cabin, and repeating the operations M times for each position;
• using an acoustic acquisition assembly to collect four audio signals during each playback, and sending the audio signals to a controller;
• denoting the four audio signals as a group;
• step S1.3:
• the controller processing the training data acquired in step S2 and constructing a lithium-ion battery safety valve opening acoustic signal recognition model;
• step S1.4:
• the XGBoost model training module using the lithium-ion battery safety valve opening acoustic signal data identified by the acoustic signal recognition model to train the XGBoost model to predict localization errors;
• step S2:
• the acoustic sensor acquiring acoustic information in the energy storage cabin in real time and transmitting to the controller, the controller using the trained battery thermal runaway acoustic source localization error compensation system to achieve real-time accurate localization of the lithium-ion battery thermal runaway acoustic source.