Implementation of state of charge and state of health estimation techniques in lithium-ion battery management systems

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Energy storage systems (ESS), specifically battery packs, or needed across a wide range of applications. ESSs are needed for the 'Smart Grid' energy storage to enable the wider use of intermittent wind and solar renewable energy. Also electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs) grows, battery technology has become increasingly important. Lithium-ion batteries are considered the best battery choice due to their high energy density and high power density. In Li-ion battery packs, a battery management system (BMS) must be utilized in order to achieve safe and reliable operation. An integral part of the BMS is estimating state of charge (SOC) and state of health (SOH) and the proposed research will focus on these two aspects. The discharge profiles of Li-ion cells are very flat and as such it is very difficult to estimate state of charge with traditional battery approaches. Nuvation Engineering is eager to support the investigation of SOC and SOH estimation models for implementation on their BMSs in order to differentiate their product in the marketplace. Research is currently required in implementing SOC and SOH estimation algorithms that have low computational cost and high accuracy.