Peak Power Control of Battery and Super-capacitor Energy Systems in Electric Vehicles

Hybrid energy systems consist of a load poweredby a source and a form of energy storage. Systems with mixedenergy supply find applications in the electric grid with renew-able and non-renewable sources, in mission critical systems suchas Mars rovers with rechargeable and non-rechargeable batter-ies and low-power monitoring systems with energy harvesting.A general problem for hybrid energy systems is the reductionof peak power consumption to ensure cost-efficient operation aspeak power draws require additional resources, adversely affectthe system reliability and storage lifetime. Furthermore, in somecases such as electric vehicles, the load dynamics are fast, notperfectly known a priori and the computation power available isoften limited, making the implementation of traditional optimalcontrol difficult. This paper aims to develop a control schemeto reduce the peak power drawn from the source for hybridenergy systems with limited computation power and limitedload forecasts. We propose a scheme with two control levels andprovide a sufficient condition for control of the different energystorage/generation components to meet the instantaneous loadwhile satisfying a peak power threshold. The scheme providesperformance comparable to Model Predictive Control, whilerequiring less computation power and only coarse-grained loadpredictions. As a case study we implement the scheme for abattery-supercapacitor system in an electric vehicle with realworld drive cycles to demonstrate the low execution time andeffective reduction of the battery power (hence temperature),which is crucial to the lifetime of the battery.