Design and further development of battery management systems (BMS) with modular and flexible structure.
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.
Battery management systems are designed in-house and existing systems are being further developed. This enables an efficient and innovative design with suitable software.
Estimating the state of charge is an essential criterion for the safe operation of a battery. The state of charge of a battery cannot be measured directly, but must be calculated from measurements of voltage and current. Fraunhofer ISE is researching methods to estimate the state of charge in real time as accurately as possible. Not only conventional methods are being deployed and further developed, but new approaches are also being examined. Model-based methods and modern filter methods allow the estimation of the state of charge for different profiles, temperatures and battery types. Our team advises and creates test profiles and models to enable a reliable estimation of the state of charge for a wide range of battery types and applications.