Battery Management Systems and State Estimation

Kalman Filter als Algorithmus  zur Zustandsbestimmung.
© Fraunhofer ISE
Kalman filter as an algorithm for state estimation.

In the field of battery management systems and state estimation, we design battery management systems and adapt them to a wide range of applications. The requirements for battery management vary, depending on the application, in the number of sensors, current range, measurement accuracy, sampling rate, communication interfaces and costs. In addition, we develop software that makes battery management the heart of every battery system. For example, we are researching algorithms to determine the state of charge (SOC) and state of health (SOH).

Development of Battery Management Systems

To ensure that batteries function properly, it is important to monitor all sensors at all times and to avoid misusing battery cells. In addition to this basic functionality, battery management systems should offer further functions.

Crush Tests

We offer advice on test design and support you in implementing additional sensors, implementing real-time capability and integrating (wireless) communication standards. Our skills also include distributed architectures and the connection of external cloud storage.

Determining the state of charge (SOC) and state of health (SOH) provides long-term, precise access to a battery's operating parameters. We implement the underlying algorithms in your systems and advise you on their implementation.

Our R&D-Services on the Topic "Battery Management Systems and State Estimation" Include:

  • Adaptation of existing and new development of hardware
  • Distributed architectures: master-slave battery management with cloud connection
  • Various communication standards: BLE, WiFi, CAN, isoSPI, UART
  • Embedding of laboratory measurement methods on small hardware, e.g. EIS
  • Implementation of algorithms for state determination

More Information on this Research Topic

 

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