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Figure 1: Mechanism for real-time diagnosis of the performance of a running battery
Figure 2: By comparing the remaining battery capacity calculated by the two calculation methods, the “storage capacityâ€, “measurement current errorâ€, and “battery internal resistance†are respectively revised.
Figure 3: Railway model using real-time diagnostics of battery performance. The current and voltage data are sent to an external PC for processing through wireless communication, and the battery capacity and deterioration degree are diagnosed.
Mitsubishi Electric announced on February 17, 2016 that it can diagnose battery status such as battery level and deterioration level in real time. This technology uses a self-developed calculation method to estimate the state of the battery in real time based on the current and voltage data of the battery in operation, and is "the world's first" (Mitsubishi Electric). In the past, there was no technology capable of real-time diagnosis of the state of a battery in use, and it was necessary to suspend the system, which often resulted in a decrease in the system operating rate.
When using this technology, the inferred error of the remaining 5% or more of the remaining battery capacity can be reduced to less than 1% (Figure 1). It can be used to diagnose solar energy, wind power generation batteries, and batteries used in automobiles, railway vehicles, and HEMS (residential energy management systems). Mitsubishi Electric plans to put the technology into practical use around 2020.
This technology is achieved by combining two existing battery diagnostic methods (Figure 2). One is the "current integration method" that calculates the power based on the current data, and the other is the "open circuit voltage method" that extrapolates the remaining battery level based on current and voltage data. The current method is to compare the “battery remaining amount†estimated by the two calculation methods, correct the parameters “storage capacity†and “measurement current error†required by the current accumulation method at any time, and the parameters required for the open circuit voltage method “inside the batteryâ€. resistance". Then use the iterative least squares and other data processing techniques to correctly infer the battery margin.
Use MCU or personal computer (PC) for data calculation. Mitsubishi Electric proposed two methods. One is to embed the MCU in the battery module for diagnosis. The other is to use the communication function to send the measured data to the PC and calculate it externally. The company conducted a demonstration of the second method at a press conference held on February 17. The battery-powered railway model was equipped with a communication function to perform battery diagnostics on an external PC (Figure 3). If you have communication capabilities, you don't need to have an MCU on every device, but this still has the problem of increased traffic.
Previously in the diagnosis of battery performance required to stop the discharge, access to another diagnostic system, so that the battery charge and discharge. On the other hand, it is difficult for batteries used in power grids and large-scale mechanical operations to stop discharging for diagnosis, and it is necessary to develop technologies that can diagnose in real time during operation. (Reporter: Sato Masaki)
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