According to an embodiment, a diagnosis method of a battery is provided. In the diagnosis method, based on an internal state of the battery at a plurality of mutually different times, a time when the internal state of the battery becomes a predetermined state after the plurality of mutually different times is estimated.

A provisioning device includes a communication module capable of communicating with a plurality of battery management systems included in the battery pack; and a processor, wherein the processor causes the communication module to wirelessly transmit a provisioning signal for switching at least one battery management system of the plurality of battery management systems to a provisioning mode, receives state information of the battery and the battery management system from the plurality of battery management systems through the communication module, and assigns an ID of a network of the battery pack and an ID of each of the battery management system based on the state information of the battery management system received through the communication module.

The disclosure relates to a method for providing an aging state of a device battery of a battery-operated device including detecting curves of operating variables of the device battery and providing at least one load factor at a determination time, providing a correction model that maps a correction variable depending on the at least one load factor, and ascertaining an aging state by evaluating the curves of the operating variables with the aid of an aging state model or an aging state observer or an aging state measurement and depending on the correction variable resulting from the at least one load factor of the device battery of the battery-operated device at the determination time.

The disclosure relates to a method for providing an aging state of a device battery of a battery-operated device including detecting curves of operating variables of the device battery and providing at least one load factor at a determination time, providing a correction model that maps a correction variable depending on the at least one load factor, and ascertaining an aging state by evaluating the curves of the operating variables with the aid of an aging state model or an aging state observer or an aging state measurement and depending on the correction variable resulting from the at least one load factor of the device battery of the battery-operated device at the determination time.

The present disclosure relates to batteries health across a fleet of machines. The battery life on a machine varies significantly according to work applications. A site has a plurality of the same machine working in various applications to fulfill a productivity requirement. More particularly, the present disclosure pertains to a balancing state of health (SoH) of batteries across a fleet of machines. The harshness of the various machine applications on a given work site is determined using a site-wide model. The model proactively tracks the work history and current battery state of health of each machine to determine appropriate assignments such that the machines rotate through the various applications on a periodic basis. Additionally, the model ensures a sufficient state of health of the battery to complete the assigned task. The reduced battery life results in downtime troubleshooting a perceived problem along with the associated additional cost. The balancing battery life across the fleet results in more consistent operation.

The present disclosure relates to batteries health across a fleet of machines. The battery life on a machine varies significantly according to work applications. A site has a plurality of the same machine working in various applications to fulfill a productivity requirement. More particularly, the present disclosure pertains to a balancing state of health (SoH) of batteries across a fleet of machines. The harshness of the various machine applications on a given work site is determined using a site-wide model. The model proactively tracks the work history and current battery state of health of each machine to determine appropriate assignments such that the machines rotate through the various applications on a periodic basis. Additionally, the model ensures a sufficient state of health of the battery to complete the assigned task. The reduced battery life results in downtime troubleshooting a perceived problem along with the associated additional cost. The balancing battery life across the fleet results in more consistent operation.

Predicting battery life including wirelessly receiving an initial state of a battery and a tracked event associated with the battery at a cloud-based server, and updating an estimate of the battery life using the tracked event.

Predicting battery life including wirelessly receiving an initial state of a battery and a tracked event associated with the battery at a cloud-based server, and updating an estimate of the battery life using the tracked event.

A lead-acid battery monitoring device includes a plurality of sensor units 20 attached to a plurality of lead-acid batteries 1 connected in series and/or in parallel and a control unit 10 that sequentially establishes wireless communication connection with the plurality of monitoring units 20. The lead -acid battery monitoring device executes a first monitoring operation in which the management unit 10 sequentially receives monitoring data including an internal resistance and a temperature of each lead-acid battery 1 from the plurality of monitoring units 20 and a second monitoring operation in which the management unit 10 sequentially receives monitoring data including the temperature of each lead-acid battery 1 from the plurality of monitoring units 20.

A remote controlled battery cell monitoring and control system that utilizes empirical and theoretical data to compare performance, sensor data, stored patterns, historical usage, use intensity indexes over time and tracking information to provide a sophisticated data collection system for batteries. This tracking is designed to better the specifications, designs, training, preventative maintenance, and replacement and recycling of batteries.