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Hybrid energy storage systems (H-ESSs), as hybridizations of batteries and supercapacitors (SCs), need to be handled by appropriate energy management systems (EMSs). Smoothness of battery current to reduce their degradation are normally the aim of the EMSs. The evolutions of SC voltage however also need to be addressed. Various approaches for handling SC voltage while managing battery current can be found in the literature. Most of the time, their limitations are achieved directly or indirectly in the EMS. This paper aims to develop a merging control scheme to include the SC control outside the EMS. This control scheme based on the inversion principle of the Energetic Macroscopic Representation is proposed for a battery/SC subsystem. Two control schemes are thus systematically deduced and then merged. The battery current reference is generated regarding their aging behavior. Meanwhile, the SC voltage reference is deduced concerning the required SCs stored energy as a function of the vehicle velocity. The proposed approach is validated by simulation in Matlab/Simulink®.

Energy management strategies are mandatory for hybrid energy storage systems in applications for electric and hybrid vehicles. Optimization–based real–time strategies are of interest since they are straightforward to optimize performance criteria. The available methods are often the combinations of adaptive mechanisms with solutions deduced by optimal control techniques such as Pontryagin’s minimum principle (PMP). This paper proposes an approach to develop a real–time strategy for battery/supercapacitor systems based on PMP and Energetic Macroscopic Representation without any need of adaptive mechanism for the co-state variable. Performances of the proposed strategy are validated by simulation.

Using supercapacitors (SCs) to configure the hybrid energy storage system (H-ESS) to extend battery life-time is promising for electric vehicles (EVs). Energy management strategy (EMS) is mandatory for such systems. Most of previous works develop improved EMS with the only one objective, normally on battery life-time. However, at least the costs on SCs operation also need to be taken into account. Generally, a methodology to develop multi-objective EMS is demanded. This paper presents a procedure to develop multi-objective EMS of H-ESS for an EV. SCs system losses are considered as the second cost function. Dynamic programming is used to give the benchmark in order to evaluate the performance of the other strategies. Simulation results validate the effectiveness of the developed off-line EMS. The dynamic programming generates a Pareto front to be used in order to compare with other on-line EMS.

In electric vehicles, supercapacitors (SC) are commonly used to perform a hybrid energy storage system (H-ESS). This approach, correctly coordinated and designed, can extend battery lifetime by limiting the battery current stress. SC are often coupled to DC/DC converters. To use the maximum energy stored in SC, high variability of the SC voltage is mandatory. Several time, the associated converter voltage ratio becomes too high and can produce instability of the system. Thus, at each time there is a minimal value for the SC voltage. This article proposes a dynamical limitation method for the SC voltage. The dynamic method is compared with a traditional constant limitation technique. Both are tested under the urban part of New European Driving Cycle with slope. The results point out that the dynamical limitation can ensure a better stability of the system regardless environment disturbance.

Nowadays energy storage is the keypoint of the development of electrical vehicles (EV) for charging time, autonomy and cost reasons. The main energy storage system for electrical vehicles is the battery and can cost up to one third of the vehicle price. Nevertheless the battery has limited power features and can be damaged by EV peak power requirements. Thus higher power density energy storage systems (such as supercapacitors) are used in combination with batteries (multisource EV). A reduced-scale EV demonstrator has been developed to present the concept of multi-source EV to high school and undergraduate students. The aim of this demonstrator is to highlight the interest of research on electric vehicle to attract students in this research topic.