Battery and Energy Management Systems#
The control in devices and systems requires continuous information about the state of the battery system. Even with the most advanced battery technologies, the user has no direct information about the internal state of the battery: What is the state of charge (SOC)? What is the state of health (SOH)? When should it be replaced? Algorithms developed at Fraunhofer ISE can estimate the state of charge (SOC) and the aging of the battery (SOH) in real time based on models and provide the user with information about these states. Aging prediction models, which can also be integrated in battery management (BMS) hardware, make it possible to assess the influence of operating strategies on the service life of the battery storage device. We develop intelligent charging and operation management strategies that can be easily integrated into microcontrollers of charge controllers, device controls, battery and energy management systems. For example, the cooling system can be controlled, error conditions can be diagnosed and connected chargers can be optimally controlled to enable battery longevity as well as rapid charging.