This paper aims at presenting an energy management strategy (EMS) based upon optimal control theory for a battery–supercapacitor hybrid power system. The hybrid power system consists of a lithium-ion battery and a supercapacitor with associated bidirectional DC/DC converters. The proposed EMS aims at computing adaptive gains using the salp swarm algorithm and load following control technique to assign the power reference for both the supercapacitor and the battery while achieving optimal performance and stable voltage. The DC/DC converter model is derived utilizing the first-principles method and computes the required gains to achieve the desired power. The fact that the developed algorithm takes disturbances into account increases the power elements’ life expectancies and supplies the power system with the required power.

Nowadays, electric vehicles are one of the main topics in the new industrial revolution, called Industry 4.0. The transport and logistic solutions based on E-mobility, such as handling machines, are increasing in factories. Thus, electric forklifts are mostly used because no greenhouse gas is emitted when operating. However, they are usually equipped with lead-acid batteries which present bad performances and long charging time. Therefore, combining high-energy density lithium-ion batteries and high-power density supercapacitors as a hybrid energy storage system results in almost optimal performances and improves battery lifespan. The suggested solution is well suited for forklifts which continuously start, stop, lift up and lower down heavy loads. This paper presents the sizing of a lithium-ion battery/supercapacitor hybrid energy storage system for a forklift vehicle, using the normalized Verein Deutscher Ingenieure (VDI) drive cycle. To evaluate the performance of the lithium-ion battery/supercapacitor hybrid energy storage system, different sizing simulations are carried out. The suggested solution allows us to successfully optimize the system in terms of efficiency, volume and mass, in regard to the battery, supercapacitors technology and the energy management strategy chosen.

This paper aims at presenting an energy management strategy (EMS) based upon optimal control theory for a battery-supercapacitor hybrid power system. The hybrid power system consists of a Lithium-ion battery and a supercapacitor with associated bidirectional DC/DC converters. The proposed EMS aims at computing adaptive gains using salp swarm algorithm and load following control technique to assign the power reference for both the supercapacitor and the battery while achieving optimal performance and stable voltage. The DC-DC converter model is derived utilizing the first-principles method and compute the required gains to achieve the desired power. The fact that the developed algorithm takes disturbances into account increases the power ele-ments’ life expectancies and supplies the power system with the required power