In this work, energy management in Battery Supercapacitor (SC) based Electric Vehicle (EV) is investigated from a control theory perspective. An Energy Management System (EMS) based on Sliding Mode Control (SMC) is proposed to distribute power suitably among the energy sources. The energy management problem is formulated in terms of power and energy of the two energy sources. The Rate of Change (RoC) of reference battery power is directly controlled by the SMCto maintain a smooth trajectory of reference battery power. The highly fluctuating load power components are managed by the auxiliary power source driven by the SC while keeping its energy within desired limits. Thus the battery is protected from sudden load surge and thereby improving its performance and enhancing its life. The control parameters of the SMC are tuned by using Cuckoo Search optimization technique. Robustness of the proposed SMC based EMS under different driving conditions is assessed by testing its performance on various drive cycles like UDDS, HWFET, SC03, Manhattan and NYCC. Real-time simulator OPAL-RT is used to implement the proposed control strategy. A performance metric based on battery State of Health (SOH) is used to study the impact of battery current change on capacity degradation of the battery. The improved performance quality indices confirm robust and satisfactory performance of the proposed SMC based EMS across a variety of driving conditions. Simulation results ensure that the proposed SMC based EMS has promising potential to reduce ageing stress on the battery and enhance efficiency of EVs.