Our Battery Health team manages the testing and assessment of our battery modules as well as live monitoring of deployed systems. To do so, we develop battery testing facilities, manage testing logistics and develop evaluation routines to determine key parameters such as State of Health. Our aim is to achieve complete insight of each battery’s condition during initial assessment and throughout its 2nd life and to increase our testing throughput, automation and capabilities.
Battery Analytics
Development of battery models and parameterisation methods
Research and development of battery screening and grouping algorithms
Optimisation of battery test protocols to reduce testing time while maximising the extractable features
Defining test plans for battery ageing tests and excecution with external partners
Product development
Evaluation and analysis of potential new battery types (e.g. thermal tests, performance tests)
Defining operational strategy for energy storage systems (e.g. derating, operation windows, safety limits)
Monitoring
Provide battery expertise for occasional analysis of monitoring data for internal support
Analyse and develop requirements for our Battery Cloud for operational efficiency and to meet evolving regulatory requirements, e.g., the battery passport
Test facilities
Contribute to the development and optimisation of testing protocols as well as the associated test requirements (hardware, environment, etc.)
Collaborate with the software development to develop full automated workflows for battery data analysis and groupings, improving efficiency and scalability in battery health monitoring and diagnostics.
Collaborate on future developments in our testing strategy including testing methods and battery handling logistics
Degree in Electrical Engineering, Chemical Engineering, Materials Science, or a related field
Established battery expertise (>3 years) in more than one of the following areas:
Battery testing (methods, standards)
Lithium-ion battery modelling (e.g., equivalent circuit models, machine learning)
Battery aging/degradation mechanisms
Analysis of test/monitoring data (e.g., cyclical data, pulse and EIS measurements)
SoC / SoH / RuL estimation algorithms
Software / Data Science knowledge is an advantage
Experience with battery testing hardware (e.g. battery cyclers, power electronics, eis) is nice to have
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