During the development of battery packs, the challenge of accurately obtaining the reliable temperature of the battery was faced. When the cells are measured at different temperatures and SOCs in the incubator, the cell temperature is relatively uniform. However, once the battery cells are put into the battery pack through the production process, the temperature uniformity will be broken again. For example, everyone understands that the bottom surface of some battery packs is water-cooled, hot and cold in summer, and hot and cold when it is just started in winter. This sudden change in temperature is extremely stressful on the battery, but this is not over, the most terrible point of the current power battery is that you do not understand it at all, and when thermal runaway can hardly be warned in advance.
At present, most of the temperature sensing technology is NTC, [Negative Temperature Coefficient, its resistance value decreases with the increase of temperature] The temperature of the upper surface of the battery measured by this sensor is different from the internal temperature, and there will be a significant temperature difference between the upper and lower levels. Does the NTC measurement case temperature represent the true temperature inside the cell? Is it possible to use a weighted average or some way to obtain a more accurate temperature of the cell by weighted average or more temperature data (at least the upper and lower dimensions of the cell)? Now NTC is often installed on the surface of the shell, there is heat transfer heat resistance, will affect the measurement accuracy and temperature response of the slow, then now the demand comes, the entire new energy industry, is very hopeful to have a more accurate temperature measurement program, quickly and accurately obtain the temperature of the cell, to the BMS or vehicle power domain controller.
To put it bluntly, the core concept of battery safety is to have a nervous system for battery measurement management, and it is necessary to have a full range of multi-dimensional online evaluation of batteries. Otherwise it will turn the battery into a black box to think, Professor Schade of Fiber Technology recently introduced a case of implanting an fsFBG sensor into an anode active material to express the expansion of the electrode with a strain signal, which inspired me greatly. Because compared with the temperature signal of the power battery, the strain signal of the power battery measured by fsFBG can detect the occurrence of thermal runaway earlier, and may really turn the effective warning of thermal runaway of the battery into a true proposition.
fsFBG simply put, a very high temperature stability of the Bragg grating, the sensor array formed by this sensor is effectively implanted into the battery system to provide early warning of battery safety, can provide extremely detailed sensor granularity indicators, now the battery almost only has two measurement methods of current and voltage (previously shared with you the ampere-hour integration and open circuit voltage) so the addition of this measured temperature, stress strain sensor can more effectively control the local thermal runaway of the battery, Gas production and so on to do a long period of early warning, equivalent to this type of sensor plus after is a nerve intelligent battery, can be detected online in various working scenarios, the application of this sensing system on the battery, I define it as the last step of human management of new energy batteries. #Car science poster##Understand car king ##新能源汽车#
