Through a clearer understanding of the components of lithium ion, various mathematical and computational models are used to better explain thermal safety. These include models that determine the individual reactions that occur inside the battery before and after exhaust and TR, such as computational fluid dynamics (CFD) simulations of battery design and packaging structure in multi-battery solutions, flammability limits, and high-throughput screening studies , To link the actual signal of the material with the system response. Similarly, in the system, use sensor fault detection feedback to circuit model parameters, data-driven methods to quantify failure probability, risk assessment through failure modes or similar methods, cloud-based fault diagnosis tools, and across different battery formats and chemistry Material trends.
However, there are some key problems in predicting TR, including its extremely low frequency of occurrence and lack of consistent meaning for thermal runaway, resulting in a mismatch between laboratory-scale test results and the actual situation, and as the size and complexity of battery test items increase , The budget for testing has been significantly increased. Therefore, pattern recognition methods such as machine learning or big data analysis can obtain a limited training data set, which results in sufficiently reliable results. On the other hand, even after careful control of the test setup and operator variability, the results of mechanical abuse test results are not always certain. In this case, it is very useful to analyze the sensitivity of system-level test results to specific design parameters. The interval of the parameters obtained from these tests is used as the input of the mathematical model and can be used to build a safety diagram showing the mutual use of the failure probability derived from each parameter
The conceptual diagram of BMS-iPROUD is shown in Figure 3. The purpose of iPROUD is not only to receive information from the BMS, but also to receive information from the load and the grid through a two-way communication channel. The goal of iPROUD equipment is to regulate the rate at which the battery receives and stores energy from the grid and the rate at which the battery supports the load. BMS has sensors for the internal state of each battery (such as voltage, temperature, impedance, etc.), monitors and manages each battery in the battery, and inputs these data into iPROUD. It uses these data to link the internal state of each battery to the functional performance of the battery, and combines the data with the information received from the load to determine the level of power support the battery can supply. It makes similar decisions about the mutual use of power grids and batteries. If the BMS detects that the internal state of any battery in the battery is abnormal, iPROUD will not allow the abnormal battery module to be charged until the battery state returns to normal.
The internal temperature of the battery is used to determine the charging process. Fast battery charging is not only convenient for electric vehicles, but also essential in grid applications. It is also an operating parameter that can increase the internal temperature of the battery, potentially accelerating the aging of the battery, pushing it into the TR and exhaust. Attempting to use surface temperature as a parameter to protect the battery from venting may be misleading and therefore harmful. The data in Figure 4 is that one battery cell (5.3Ah) in the battery starts to charge at a rate close to 2C. The battery in this example is usually charged at a rate of 0.7C, and it takes about 120 minutes to be fully charged after being fully discharged. When the temperature rises above 35°C, iPROUD converts the current to zero to cool the battery internally, and limits the charging rate to 0.7C and 0.5C at other times. The total time for the battery to be fully charged is 95min. On the contrary, if the battery surface temperature is selected as a parameter and its limit is set to 35°C to cut off the current, the temperature will increase to a higher value, which will accelerate the battery aging and cause the battery to run out of thermal control. iPROUD takes temperature and battery voltage as control parameters, and improves battery management through the battery's electrolyte and charge transfer resistance and coulomb capacity, so as to obtain higher safety, long life, and energy storage and power transmission efficiency.