BatteryMAP System Dashboard
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With BatteryMAP, your ESSs will have
at Cell Level
The technology of BatteryMAP can accurately
identify the failure and risk of a single cell in a battery cluster (eg: internal short circuit), and take different mitigation strategies for different stages of risk generation.
The data of batteries can be collected remotely and in real time. Alerting parameters and failure ranks can be set situationally. The person responsible can be notified by cell phone messages about the battery failure.
Compared with other cloud platform systems, the competitive advantages of BatteryMAP are:
The algorithm is more accurate.
General artificial intelligence algorithms are completely based on data, while BatteryMAP uses an algorithm that combines big data and electrochemical models to have higher accuracy in battery failure prediction. In addition, BatteryMAP enjoys unique resources, as its models are trained on massive amounts of real-world usage data and tested in real-world applications. Moreover, in actual use, the model will also update itself according to the usage data.
The technology of BatteryMAP can accurately identify the failure and risk of a single cell in a battery cluster (eg: internal short circuit), and take different mitigation strategies for different stages of risk generation.
For example, if an internal short circuit is found in the initial stage, the battery is to be saved; If an internal short circuit is found in the intermediate stage, enough time is gained to schedule the replacement therefore to avoid actual failure and consequent emergency response; If an internal short circuit is found in the final stage, the scale and extent of thermal runaway can be reduced.
As mentioned above, the collaborative management of the energy storage system network is a function that strata developers wish but have not yet made available.