Hybrid Energy Storage System interface for Electric Vehicles

This paper proposes a new control configuration of hybrid energy storage system (HESS) using a battery pack and a supercapacitor for electric vehicle (EV). The HESS is designed based on bidirectional quasi-Z-source inverter (QZSI) and a DCDC converter. The HESS configuration with its modeling is presented in this paper. The operation modes of HESS for EV and its control scheme using fractional order PI controller (FOPI) are presented. FOPI controller is combined with a filtering technique to contribute to battery degradation mitigation. The fluxweakening method is applied to provide correct operation with the maximum available torque at any speed request within current and voltage limits. The simulation results verify the performance and effectiveness of the HESS topology. The results also point out the ability of the inverter to give a fast response to the mechanical load and provide a DC bus constant voltage over the powerdemand profile. The proposed HESS with these types of controller and converter can globally enhance the performance of the EV by allowing the efficient energy use of the battery for a longer distance coverage and extending its driving range.

The power management capabilities of hybrid energy storage systems offer several advantages for EVs, including improved performance, longer battery life, and reduced cost. HES technologies which combine Li-ion cells with ultra-capacitors (UC), are developing as just a possible alternative to the constraints of conventional ESS for conserving electricity. Lithium-ion batteries have a limited cycle life, meaning that they gradually degrade with each charge-discharge cycle. This can reduce the overall lifetime of the ESS and require more frequent replacements, adding to the cost and environmental impact of EVs. To circumvent those constraints, mixed battery packs combining battery technology as well as superconductors are being developed. To improve the design and control of hybrid energy storage systems for electric vehicles (EVs), a bi-level multi-objective framework has been proposed. A Bi-level multi-objective design and control framework, incorporating NSGA-II and fuzzy logic control, to obtain an optimal sized hybrid energy storage system and corresponding power management strategy. This dynamic and multi-objective architecture may achieve optimum solution hybrids battery bank as well as a matching significant power scheme one at a moment through integrating non-dominated sorting genetic and fuzzy logic control methods. To evaluate the effectiveness of the proposed bi-level multi-objective framework, Pareto optimal solutions of different hybrid energy storage systems are obtained. This approach can lead to significant improvements in the performance and efficiency of hybrid energy storage systems, making them more suitable for EVs and other applications that require high-performance energy storage solutions. Index Terms—Batteries, ultra capacitors, recursive imprecise input, non – linear and non optimisation, and e – mobility

This work presents a battery-ultracapacitor hybrid energy storage system (HESS) for pulsed loads (PL) in which ultracapacitors (UCs) run the pulse portion of the load while the battery powers the constant part of the load. Energy stored in UC depends upon the square of its voltage that’s why an active parallel hybrid topology with two bidirectional converters (BDC) is employed here that assigns UC a separate BDC to control its voltage between an upper and lower limit as per-requisite. The other converter is connected between the battery and DC-link to provide a distinct control of the battery. A MATLAB/Simulink model is developed to minimize the factors affecting the battery life such as capacity rate (C-rate), depth of discharge (DoD), and temperature rise due to PL by controlling the operating modes of the BDCs in which voltage of the UC and state of charge (SoC) of the battery are control variables. A constant output voltage across the load is maintained through feedback control. A detailed comparative analysis, among battery-alone, UC-alone, and battery-UC hybrid modes is performed which signifies that the proposed system is 55% lower in cost than its counterparts. The analysis shows that the proposed HESS reduces 50% capacity of a lead-acid battery, which is otherwise necessary to withstand the pulsating loads. Moreover, the performance of the HESS is also tested for electric vehicle (EV) load by hybridizing a high-voltage lithium-ion battery pack with a UC bank which confirms its suitability for EV applications.

Hybrid energy storage system (HESS) having sources with complimentary characteristics is preferred in electric vehicle application, so as to fulfill the requirements such as reduced weight, long life of sources and improved dynamic response. In this paper, electric vehicle (EV) power conversion system is implemented with HESS which is comprised of battery and ultracapacitor (UC). UC has high power density and more life cycles compared to battery and battery has high energy density. Here UC delivers high current during acceleration and it can take in large and sudden current during regeneration and hence it improves the battery life. Bidirectional converter is used to drive the inverter driven induction motor (IM). Sources are charged during regenerative braking and hence it increases the efficiency of EV. An experimental prototype of EV power conditioner is developed and tested.

This paper presents the modelling, design and power management of a hybrid energy storage system for a three-wheeled light electric vehicle under Indian driving conditions. The hybrid energy storage system described in this paper is characterized by effective coupling of Li-ion battery (primary energy source) and ultracapacitor (auxiliary source) interfaced with an efficient bi-directional converter. A design methodology related to vehicle modelling, choice of motor rating, converter design, sizing of Li-ion battery and ultracapacitor pack for the Indian driving cycle are presented. An improved real-time power-split management control strategy is proposed for proper power flow control of the hybrid energy storage system under various operating modes. The hybridized energy storage system with proposed control strategy improves the life of the battery and helps in effective utilization of the ultracapacitor. Furthermore, a relative comparison of the hybrid energy storage system with the battery energy storage system based on battery parameters and capital cost is also presented. Simulations are carried out in MATLAB/Simulink environment to verify the effectiveness of the proposed control strategy with modelled system components of three-wheeled light electric vehicle. A downscaled experimental prototype is built to validate the power-split between hybrid energy storage systems.

In recent years, the electric vehicles (EVs) power management strategy has been developed in order to reduce battery discharging power and fluctuation when an EV requires high and rapid discharging power due to frequent stop-and-go driving operations. A combination of lithium-ion battery and supercapacitor (SC) as the EV’s energy sources, known as a hybrid energy storage system (HESS), is a promising solution for fast discharging conditions. Effective power management to extensively utilize HESS can be developed if future power demand is accessible. A vehicular network as a typical form of the currently developed internet of things (IoT) has made future information obtainable by collecting information on surrounding data. This paper proposes a power management strategy for the HESS with the support of IoT. Since the obtained information from the vehicular network could not directly be used to improve HESS, a two-level control structure has been developed to perform future data prediction and power distribution. A fuzzy logic controller (FLC) is utilized in level one control structure to manage a HESS power split based on future information. Since FLC requires future information as a reference input, the future information is obtained by using an artificial neural network (ANN) in level two control structure. The ANN provides a direct prediction that could approximate the future power demand prediction with the assumption that the vehicular network scenario is deployed to obtain surrounding information. Simulation results demonstrate that the average discharging battery power and power variation are reduced by 46.1% and 52.3%, respectively, compared to the battery-only case.

This paper presents the control of a hybrid energy storage system performance for electric vehicle application. The hybrid energy storage system helps to enhance the life of battery by reducing the peak power demand using an auxiliary energy storage system (AES) based on super capacitor and a bidirectional buck-boost converter. Further, the performance of an electric vehicle in various environments like acceleration, regenerative braking and normal speed of operation are simulated using the Saber RD software. The LabVIEW interfaced with Arduino controller is used to analyze the prototype hybrid energy storage system. The simulation results showed that the proposed hybrid energy storage system helps to decrease the peak power demand up to 54% from the battery system. The experimental results are presented, validating the simulation results.

Electric Vehicles (EVs) are the best alternative to deal with fossil fuel and air pollution crisis. These vehicles have an electrical propulsion system which is connected to an Energy Storage System (ESS). Internal combustion engine propulsion system (parallel hybrid EV), engine-generator (series hybrid EV), or fuel cell system (fuel cell hybrid EV) may also exist in an EV. High performance ESS is needed as a result of electric power requirement. The batteries, conventional ESS, have high energy and low power specifications for use in EVs. Another candidate for EV's ESS is ultra-capacitor (UC). The ultra-capacitors have very low energy and high power specifications. In recent years, some designs have been proposed to combine batteries and ultra-capacitors to develop a hybrid energy storage system (HESS) with high energy and high power specifications. In this kind of ESS, the power fluctuation of the battery is reduced and the life of the battery is increased. In this study, the behavior of a heavy duty EV with an ESS is compared with a HESS one. This comparison is done in 5 different driving cycles which have different level of aggressiveness. The results show that the vehicle performance, the energy saving characteristics and the battery life criteria improvement values are related to the aggressiveness characteristics of driving cycles.

To solve the problem of battery capacity degradation caused by high current magnitudes and frequent current variations in electric vehicles (EVs), a hybrid energy storage system (HESS) incorporating high energy density storage (battery) and high power density storage (ultracapacitor) is proposed. The HESS contains a multi‐port DC‐DC converter, which controls the energy flow among the battery pack, the ultracapacitor (UC) pack, and the port of output. Considering the state of charge (SOC) of UC, the speed, and demand power of EV, an energy management strategy (EMS) based on fuzzy logic control (FLC) for the HESS is proposed in this paper. According to the strategy, the battery pack serves as a base power source while the UC pack serves as a transient power source so as to smooth the battery pack current and prolong the battery life. Simulation and experiment results illustrate the effectiveness of the proposed strategy for UC/battery HESS in EVs. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

The electrification of transportation has spurred the development of advanced energy storage systems to meet the dynamic demands of electric vehicles (EVs). Batteries alone often fall short in handling peak load currents and regenerative energy, leading to reduced lifespan and performance degradation. This study proposes a hybrid energy storage system (HESS) combining ultracapacitors (UCs) and lithium-ion batteries to improve efficiency and reliability in induction motor (IM)-driven EVs. A real-time energy management system (EMS) based on rule-based logic dynamically allocates power between UCs and batteries. The model is validated through MATLAB/Simulink simulations and experimental setups. The results show that the HESS configuration significantly enhances battery longevity, improves vehicle acceleration, and reduces energy losses compared to battery-only systems.

This paper proposes a distributed rule‐based power management strategy for dynamic power balancing and power smoothing in a photovoltaic (PV)/battery‐supercapacitor hybrid energy storage system. The system contains a PV system, a battery‐supercapacitor hybrid energy storage system (HESS), and a group of loads. Firstly, an active compensation technique is proposed which improves the efficiency of the power smoothing filter. Then, a distributed supervisory control technique is employed that prevents the BESS and SC from SOC violation while maintaining the balance between generation and load. To this end, the system components are divided into three different reactive agents including an HESS agent, a PV agent, and a load agent. These agents react to the system changes by switching their operational mode upon satisfying a predefined rule. To analyse the hybrid dynamical behaviour of the agents and design the supervisory controllers, the agents are modelled in hybrid automata frameworks. It is shown that the proposed distributed approach reduces the complexity of the supervisory control system and increases its scalability compared to its equivalent centralized method. Finally, the performance of the proposed approach is validated using a test system simulated in MATLAB/Simulink.

Hybrid Energy Storage System (HESS) are commonly used when a combination of features and advantages from different energy storage devices are needed. Due to their characteristics, when batteries and Supercapacitors (SC) are implemented in HESS they become a good option for Electric Vehicle (EV) applications. This paper presents a bidirectional DC-DC converter as an interface between the battery and the SC, this will allow the control of the power flow. A tri-state operation for a bidirectional Buck-Boost converter is proposed in order to improve the performance of the control and reduce losses in the HESS.

This paper proposes a State of Charge (SOC) balancing control combined with flux-weakening for two-battery high-efficiency energy conversion system (HEECS) chopper-based powertrain. The HEECS chopper has an advantage of very high DC-DC power conversion efficiency using two batteries. This HEECS chopper based EV power train can realize longer driving range by changing the DC bus voltage depending on the EV speed [1]. However, SOCs of batteries can be imbalance because the driving pattern is not predictable. This paper proposes an effective method for balancing SOCs by modifying HEECS chopper’s control according to the driving speed. Simulation results show the proposed method extends driving range by 2.8% compared with the conventional SOC balancing method. The SOC difference is very small when the one of SOCs become zero.

The main purpose of this paper is to describe a novel power management control strategy for battery and supercapacitor hybrid energy storage system with the objective that the load power demand would be distributed into the energy storage devices in a way that each device can be utilized optimally. The paper describes the design and control of such an on-board hybrid energy storage system. The specific control strategy is designed based on a fuzzy-logic controller (FLC), which offers the advantage of flexibility and robustness and has been widely applied to the energy management or power distribution of multiple power sources system of an electric vehicle, to avoid the low efficiency operation region of every power source and achieve high efficiency without degrading the mechanism performance. However, prior experience fuzzy logic supervisory control is often difficulty in realizing the optimal distribution between battery and supercapacitor. In the presented research, an optimization method based on gold ratio cut-off rule is proposed to design the degree of hybridization (DOH) and membership functions of the fuzzy controller, to realize the optimal performance of fuzzy logic controller. The proposed optimization method is simple and effective, and can be applied to the practical hybrid system directly. Finally, the effectiveness of the proposed method was examined by using ADVISOR simulation platform, and in which the hybrid energy storage system was developed and embedded into the electric vehicle model. The model parameters were gained from the tested vehicle. Simulation results have shown that the proposed method can efficiently distribute the power between battery and supercapacitor to realize the design objective set forth.

Hybrid Energy Storage Systems (HESSs) are based on different storage elements such as batteries or ultra capacitors (UC), aiming to implement a system with high energy and power density. These HESSs using multi-modular power converters to incorporate in each power electronics module a different storage element and then, these modules are interconnected to create the total system. On the other hand, the Modular Multilevel Series Parallel Converter (MMSPC) not only allows dynamic interconnection among the modules in series connection but also in parallel connection. This extra switching state among the modules allows new features and operation modes. In this paper, a HESS based on MMSPC topology is presented. The novel HESS-MMSPC topology is simulated with UC and batteries as storage units, and this proposed system is interconnected to an electrical grid. The control strategy and evaluation of the operation of the proposed system are presented.