Abstract:

The forecasting of SOH (state-of-health) and RUL (remaining-useful-life) of batteries is of significant interest with great environmental and economic effect due to the continuous increase in the areas of their application, aiming at improving the people's quality of life and use of green energy. That was the reason research teams from two Bulgarian universities (Plovdiv University “Paisii Hilendarski” and Technical University–Sofia) to start a project “Hybrid and fusion prediction оf the functionality of energy converting elements”. The project started in 2021 and its aim is to create and theoretically substantiate new hybrid and fusion models for high accuracy predictive evaluation of performance and resource of energy converting elements, batteries in particular.

The scientific objectives of the project will be realized through the use of new and innovative methods:
• Innovative techniques for measuring and processing the parameters of the batteries needed to create hybrid and fusion models and deep training of the neural network:
- implementation of approaches to increase the accuracy of measurement;
- a modern method for processing and analysis of the data obtained from thermal imaging and determining the rate of the temperature rise at a given point - design and development of specialized software.
• Innovative software method for determining the degree of battery performance.

Project results will be included in a new course “Battery state-of-health (SOH) estimation” which will be uploaded on the Internet-based performance support system DIPSEIL. The course will be offered to master's students majoring in "Renewable Energy Sources and Energy Efficiency" and "Electricity Efficiency" at Plovdiv University and “Electronic systems for hybrid and electric cars” at Technical University -Sofia. Two innovative instructional strategies will be used during the training: project-based learning and inquiry-based learning. Thus, students will not only acquire knowledge but also learn to solve problems, to plan and carry out an experiment to investigate a particular problem. For this purpose, during the laboratory exercises, students will be able to use the developed unique automated system for accelerated aging and remote monitoring of battery parameters also all equipment purchased under the project.

Keywords:

Lithium-ion power battery, remaining useful life, state of health.