Predictive Control System to Maximize Lifetime of Hybrid Fuel Cells
Challenge
The vast majorities of today’s Battery Management Systems (BMS) for commercial lithium ion battery modules are based on empirical models of the lithium ion cell. Their prediction capabilities are limited and they cannot be used to estimate the State of Health (SOH), the Remaining Useful Life (RUL) and the Aging of the cells.
The main challenge to reduce the total cost of ownership concerns an optimized management of electrochemical power sources through adaptive control strategies and prognostic capabilities.
Solution
Genport designs and realizes hybrid fuel cells (HFC) combining smart energy storage systems based on Li-ion batteries with Proton Exchange Membrane (PEM) fuel cells. In order to improve reliability and lifetime, Genport has developed an algorithm capable to predict internal states (SOH, RUL) of lithium ion batteries based on their electro-chemical model (ECM).
Within HYPEMLIFE, Genport will embed a reduced order version of the original ECM into the STM32 high-end board.
The STM32 will communicate with the Li-ion battery and PEM fuel cell and will read actual voltage, current and temperature values for the battery; from those variables, HIPEMLIFE algorithm will continuously detect the internal states of the hybrid power source.
FED4SAE Support
FED4SAE has enabled us to further a collaboration with Intel; receive support from BME’s Department of Electron Devices; receive advice on the management of innovation from Blumorpho; and fund R&D. Using Intel’s Myriad 2 platform, we were able to finalise a proof of concept and move on to a design-to-cost phase. BME has assisted us with advice on heat dissipation for LED arrays.
Impact
HYPEMLIFE prognostics capabilities will minimize the overall cost of energy and improve the power quality of hybrid power sources while matching uncertainty of renewable energy sources with variability of load profile.
Integrated inside a BMS the prognostic tool will provide high precision real time estimations of important internal states of the battery. It will also add diagnostic capabilities embedded inside a battery tester by identifying latent faults in the cells.
The collaboration with ST Microelectronics and Fraunhofer Institute will move Genport to the forefront in the design of advanced electronic & control solutions to provide better power solutions to the cleantech industry.