GenSOH
We offer an advanced and highly precise real time estimator of state of charge (SOC) and state of health (SOH) for lithium ion batteries.
The algorithms are based on an accurate electro-chemical model of the lithium ion cell.
It can be integrated in the micro-controller of existing BMS or as a higher level separate micro-controller that communicates with the BMS via CAN. The actual version has been jointly embedded in the SMT32 series within the EU project FED4SAE.
GENSOH estimates additionally cycle life and calendar life at different ambient temperatures, depth of discharges, C- rates and initial SOC.
Accuracies are within 1% for SOC and 2% for SOH throughout the entire life of the battery.
The applications span from automotive to stationary.
Technology Advantages
Lithium Ion batteries are one of the key components of the green revolution and it is of paramount importance to know, in real time, how much charge remains in the battery (SOC) and, as all batteries age with time, what is the remaining total capacity (SOH) of the battery. SOC and SOH are difficult to estimate accurately because they depend both on inaccessible internal physical states of the battery.
GENSOH is a suit of algorithms based on an advanced physical / electro-chemical model of a Lithium Ion cell that is able to estimate accurately in real time SOC and SOH from measurements of voltage, current and temperature of the cells that make the battery.
GENSOH code is optimized to run in real time directly on the BMS or on a separate micro-controller communicating with the BMS via CAN.
Differently from most of the methods used by existing BMSs that require the Lithium Ion battery to be periodically recharged at 100% in order to keep the accuracy at an acceptable level, GENSOH accuracy in estimating both SOC and SOH does not decrease with time thanks to its detailed physical based model of the lithium ion cell.
GENSOH error in estimating SOC is less than 1%, whereas in estimating SOH is less than 2%. These accuracies are preserved throughout the entire life of the battery pack. For a comparison, existing methods have accuracies that are often higher than 5-15% when the battery has not been fully recharged in the recent past.
GENSOH can be used also to estimate cycle life and calendar life of the battery at different storage and cycling conditions.
GENSOH has been validated within the EU funded project FED4SAE at the Fraunhofer Institute.
Key Features
- Electrochemical model based State of Charge (SOC) and State of Health (SOH) real time estimator for Lithium Ion battery packs
- Electro-chemical model based
- Can be integrated in existing BMS or in higher level micro-controllers
- Does not require frequent full recharge of the battery to retain high accuracy
- Calendar life estimation
- Cycle life estimation
