Hybrid Electric Vehicle Battery Research Articles

Power Sharing Control Algorithm for Direct Integration of Fuel Cells in a Dual-Inverter Electric Vehicle Drivetrain

Fuel cell (FC)-battery hybrid electric vehicles (EVs) are an alternative to emergent battery EVs. Normally, a dc–dc converter is used to connect the low-voltage dc output of the FC to the high-voltage EV battery and ensure that a slow-changing unidirectional power flow is maintained from the FC. This article proposes to directly integrate the FC as one of the two energy sources in a dual-inverter-based EV drive. A conventional EV battery is used as the second energy source. A power sharing algorithm is introduced, which allows the dual-inverter drive to be modulated such that unidirectional power flow is maintained from the FC. In addition, power flow is controlled such that the minimum FC power to avoid its unnecessary shutdown is maintained under all operating points of an EV drive cycle, including regenerative braking. A key aspect of this algorithm is the injection of motor reactive current as a means to achieve desired FC power transfer during fast mechanical power reduction transients or when low mechanical power is required from the drive. This method allows for the motor to achieve fast mechanical power transients while respecting the slowly changing power reference of the FC.

Design of Solar and Battery Hybrid Electric Vehicle Charging Station

Microgrids have emerged as a new way to integrate and use large-scale distributed power to provide electricity to isolated locations, such as islands and villages. A utility engineering microgrid structure is designed to provide fast response and efficient operation by analyzing hybrid power systems and fuzzy-PI-based control techniques. This project aims to design a solar photovoltaic (PV)-battery-diesel generator-based hybrid power system employing a Sepic converter. The Perturb and Observe algorithm is used for maximum power extraction from solar panel. A lithium-ion battery is utilized as a storage battery in this system, which may be charged by the PV source. When the storage battery is depleted and PV generation is unavailable, the charging station uses the grid and a diesel generator. The generated voltage is synchronised at the Point of Common Coupling (PCC) to achieve continuous charging. The simulation is done in MATLAB/Simulink. The simulation output of using the PI control strategy is compared with the fuzzy-PI control strategy. This demonstrates the efficacy of the fuzzy-PI control method.

A Real-Time Load Prediction Control for Fuel Cell Hybrid Vehicle

The development of hydrogen energy is an effective solution to the energy and environmental crisis. Hydrogen fuel cells and energy storage cells as hybrid power have broad application prospects in the field of vehicle power. Energy management strategies are key technologies for fuel cell hybrid systems. The traditional optimization strategy is generally based on optimization under the global operating conditions. The purpose of this project is to develop a power allocation optimization method based on real-time load forecasting for fuel cell/lithium battery hybrid electric vehicles, which does not depend on specific working conditions or causal control methods. This paper presents an energy-management algorithm based on real-time load forecasting using GRU neural networks to predict load requirements in the short time domain, and then the local optimization problem for each predictive domain is solved using a method based on Pontryagin’s minimum principle (PMP). The algorithm adopts the idea of model prediction control (MPC) to transform the global optimization problem into a series of local optimization problems. The simulation results show that the proposed strategy can achieve a good fuel-saving control effect. Compared with the rule-based strategy and equivalent hydrogen consumption strategy (ECMS), the fuel consumption is lower under two typical urban conditions. In the 1800 s driving cycle, under WTCL conditions, the fuel consumption under the MPC-PMP strategy is 22.4% lower than that based on the ECMS strategy, and 10.3% lower than the rules-based strategy. Under CTLT conditions, the fuel consumption of the MPC-PMP strategy is 13.12% lower than that of the rule-based strategy, and 3.01% lower than the ECMS strategy.

Design and development of auxiliary energy storage for battery hybrid electric vehicle

This paper presents a design of capacity of supercapacitor and current control for a real-scale battery hybrid electric vehicle using an acceleration and deceleration scheme. In the MATLAB/SIMULINK model, the supercapacitor current control strategy is explained and implemented. The proposed strategies' performances are evaluated by running simulations with the Extra Urban Driving Cycle and the Urban Dynamometer Driving Schedule driving cycles to examine speed tracking performance, supercapacitor current control performance, battery voltage variation, power, and energy consumption. When compared to a full-scale battery electric vehicle, the advantages are highlighted. The viability and feasibility of the proposed control strategies are then validated using a small-scale simulation and experiment. The results show that the vehicle's applicability under deceleration-based design contributes the lowest battery energy- and power consumption and voltage variation of the battery against the other schemes.

Novel Approaches for Energy Management Strategies of Hybrid Electric Vehicles and Comparison with Conventional Solutions

Well-designed energy management strategies are essential for the good operation of Hybrid Electric Vehicles (HEVs) in terms of fuel economy and pollutant emissions reduction, regardless of the specific powertrain architecture. The goal of this paper is to propose two innovative supervisory control strategies for HEVs derived from different optimization algorithms and to assess HEVs’ fuel consumption reduction (compared to conventional vehicles). These approaches are derived from the literature and modified by the authors to present novel algorithms for the optimization problem. One is based on Dynamic Programming (DP), here referred to as the Forward Approach to Dynamic Programming (FADP) and introduces a different implementation of the DP to achieve computational and accuracy benefits. The other is based on the Equivalent Consumption Minimization Strategy (ECMS) approach, and it adapts to the latest driving conditions using information gathered in a finite-length backward-looking horizon. These techniques are used to achieve the optimal power share between the thermal engine and the battery of a parallel HEV. Their performances are compared and analysed in terms of achieved fuel economy and computational time with respect to conventional DP and Pontryagin’s Minimum Principle (PMP) approaches.

Development of a plug-in fuel cell electric scooter with thermally integrated storage system based on hydrogen in metal hydrides and battery pack

The thermal management of lithium-ion batteries in hybrid electric vehicles is a key issue, since operating temperatures can greatly affect their performance and life. A hybrid energy storage system, composed by the integration of a battery pack with a metal hydride-based hydrogen storage system, might be a promising solution, since it allows to efficiently exploit the endothermic desorption process of hydrogen in metal hydrides to perform the thermal management of the battery pack. In this work, starting from a battery electric scooter, a new fuel cell/battery hybrid powertrain is designed, based on the simulation results of a vehicle dynamic model that evaluates power and energy requirements on a standard driving cycle. Thus, the design of an original hybrid energy storage system for a plug-in fuel cell electric scooter is proposed, and its prototype development is presented. To this aim, the battery pack thermal power profile is retrieved from vehicle simulation, and the integrated metal hydride tank is sized in such a way to ensure a suitable thermal management. The conceived storage solution replaces the conventional battery pack of the vehicle. This leads to a significant enhancement of the on-board gravimetric and volumetric energy densities, with clear advantages on the achievable driving range. The working principle of the novel storage system and its integration within the powertrain of the vehicle are also discussed.

State-of-the-art review of fuel cell hybrid electric vehicle energy management systems

<abstract> <p>The primary purpose of fuel cell hybrid electric vehicles (FCHEVs) is to tackle the challenge of environmental pollution associated with road transport. However, to benefit from the enormous advantages presented by FCHEVs, an appropriate energy management system (EMS) is necessary for effective power distribution between the fuel cell and the energy storage systems (ESSs). The past decade has brought a significant increase in the number of FCHEVs, with different EMSs having been implemented due to technology advancement and government policies. These methods are broadly categorised into rule-based EMS methods, machine learning methods and optimisation-based control methods. Therefore, this paper presents a systematic literature review on the different EMSs and strategies used in FCHEVs, with special focus on fuel cell/lithium-ion battery hybrid electric vehicles. The contribution of this study is that it presents a quantitative evaluation of the different EMSs selected by comparing and categorising them according to principles, technology maturity, advantages and disadvantages. In addition, considering the drawbacks of some EMSs, gaps were highlighted for future research to create the pathway for comprehensive emerging solutions. Therefore, the results of this paper will be beneficial to researchers and electric vehicle designers saddled with the responsibility of implementing an efficient EMS for vehicular applications.</p> </abstract>

Disturbance and Uncertainty-Immune Onboard Charging Batteries With Fuel Cell by Using Equivalent Load Fuzzy Logic Estimation-Based Backstepping Sliding-Mode Control

Proton exchange membrane fuel cell (PEMFC)/battery hybrid electric vehicle is considered as promising transportation due to its eco-friendly characteristics. This article investigates a fuzzy logic (FL)-based adaptive backstepping sliding-mode control (BSMC) approach to generate stable charging current and voltage for battery charging applications on a non-plug-in PEMFC vehicle. An adaptive BSMC is proposed to address nonlinearities and disturbances caused by dc/dc buck converter, PEMFC, and equivalent load variations of batteries. Moreover, an FL-based approximation is utilized to estimate the time-varying equivalent load of batteries through the adaptive laws obtained by the defined Lyapunov function and can offer assistance estimating the state of charge (SOC) of batteries. Simulation comparisons between a proportional-integral (PI) control and the proposed FL-based adaptive BSMC were executed subsequently under certain conditions to validate the efficacy. Finally, experiments on the PEMFC/battery hybrid power system scaling prototype via NI (PCI-6229)-LabVIEW platform were implemented to test the charging performance of the proposed approach. The comparative results indicated that the FL-based adaptive BSMC method could regulate charging current and voltage against disturbance and uncertainty and estimate the equivalent load of batteries accurately.

Review and Recent Advances of Oxygen Transfer in Li‐air Batteries

AbstractThe development of high performance and low weight energy storage devices has been recently geared towards new energy batteries for electric and hybrid electric vehicles. Li‐air batteries are considered as an emerging energy source for electric cars because of their attractive theoretical specific energy of 11,400 Wh kg−1. Oxygen, as the positive electrode reaction substance of Li‐air battery, predominantly affects the dynamic performance of the battery and its diffusion is an important factor limiting the discharge process. Based on the resistance of oxygen transmission, the characteristics and influence of the Li‐air batteries are reviewed in this paper. The research on oxygen selective membrane, oxygen dissolution and transfer in positive electrode and electrolyte, structure of positive electrode and oxygenated additive in electrolyte are discussed to narrow down the internal mechanism factors that influence the Li‐air battery performance and service life. By discussing pathways to reduce the oxygen transmission resistance and hence improve the performance and life of the battery, we provide future perspectives on the application of Li‐air battery in electric vehicular power systems.

Structural design and thermal performance analysis of hybrid electric vehicle battery pack cooling system

In this paper, the flow channel structure and battery of battery cooling system are taken as the research object, and the heat transfer simulation is carried out. In order to analyze the temperature and influencing factors of battery pack in the initial scheme of cooling system structure at high ambient temperature of 40 °C, 50 °C and 60 °C, the temperature of battery pack under many working conditions is simulated, and then the optimization scheme is put forward, and the feasibility of the two schemes is compared with that of the initial scheme.

Identifying Parameters from Discharging and Relaxation Curves of Lithium-Ion Batteries Using Porous Electrode Theory

In order to improve the performance of Lithium-ion secondary batteries (LiBs) for electric vehicles and hybrid electric vehicles, it is very important to understand the internal transport phenomena and resistance under a high rate condition to increase power density. Especially, it is important to focus on the actual porous electrode structure, and the Li ion and electron conductivity have to be evaluated by the effective conductive path with the actual electrode material properties. Thus, the numerical simulation of electrochemical reaction and mass transport in the electrode layer are needed to design a heterogeneous porous structure which consists of active material, conductive material and binder. Then, the values of parameters in this model are essential for accuracy of it. However, some parameters cannot be measured precisely in experiment, especially, reaction rate constant, tortuosity of the separator, Li+ diffusion coefficient, and transport number in the electrolyte are treated as literature values or ex-situ results. In this study, we established a method of identifying these parameters by using experimental data in various conditions and a complex method. Further, this approach was applied to 1D LiB simulation. Fitting the experimental data of some SOC and some discharge rate conditions was carried out. Additionally, RMSE (Root Mean Square Error) to judge this fitting was evaluated. From these results, it was concluded that the parameters can be identified. In addition, with the identified parameters, the optimal electrode structure for a high-output power density cell was designed automatically.

Investigation of Forced Convective and Subcooled Flow Boiling Heat Transfer Coefficients of Water-Ethanol Mixture: Numerical Study

The subcooled flow boiling is related to the operation of electronic devices, Hybrid electric vehicle (HEV) Battery module and small catalytic reactors. It is well known that the operational temperature must be maintained to avoid any malfunction of these heat dissipative devices. In this paper the forced convective and subcooled flow boiling heat transfer coefficients of water-ethanol mixture is determined numerically by Volume of fluid analysis (VOF). The interaction between liquid and local vapour is analysed by solving the bubble volume of fraction in the numerical study. Crank Nicolson implicit scheme is used for discretizing the scalar convection equation for bubble void fraction and transforming into algebraic equation. Thomas Algorithm is used to solve the algebraic equations of bubble void fraction. The corrector predictor equation method is used to solve for bubble void fraction when the value obtained is less than 0 or exceeds 1. The thermodynamic and Thermophysical properties are substituted in the x-momentum and energy equation to determine the values of pressure drop, velocity and temperature of the fluid. From the temperature values, the subcooled flow boiling heat transfer coefficient is obtained. It is found that the addition of ethanol to water decreases the forced convective and subcooled flow boiling heat transfer coefficient of the water-ethanol mixture. The numerically determined heat transfer coefficient of water ethanol mixture is compared with that of the experimental results. The average deviation between the experimentally determined and numerically determined subcooled flow boiling heat transfer coefficient of water ethanol-mixture is found to be 24.13%.

Stereotaxically constructed graphene/nano lead composite for enhanced cycling performance of lead-acid batteries

Stereotaxically Constructed Graphene/nano Lead (SCG-Pb) composites are synthesized by the electrodeposition method to enhance the high-rate (1 C rate) battery cycle performance of lead-acid batteries for hybrid electric vehicles. When the SCG-Pb addition ratio is 1.0%, the initial discharge capacity of the battery reaches the maximum (185.61 mAh g−1, 0.1C rate), which is improved by 23 % compared with the control battery (without carbon). The battery still maintains 73 % of the initial discharge specific capacity after 120 cycles at 1 C rate. Compared with the control battery, the cycle performance at 1 C rate is considerably improved. Comparing SCG-Pb with the other two carbon materials (SCG, ACET), we find that SCG-Pb battery shows the highest initial discharge capacity and the longest cycle life under the 1 C rate condition. The SCG-Pb has good conductivity, rich pore structure and excellent dispersion in negative electrode active material (NAM), SCG-Pb can construct an efficient conductive network in NAM. This is conducive to the ion exchange between the negative active substance and the electrolyte, accelerates the dynamic process of the negative electrode, effectively, inhibits the irreversible sulfation of the negative electrode, hence improving the battery capacity and cycle life.

Development of hybrid thermal management techniques for battery packs

In this study, the thermal management issue of electric vehicle and hybrid electric vehicle battery pack is studied. Passive and hybrid techniques are developed and used in the battery pack. Multiple delta winglet vortex generators are introduced to enhance turbulence before the air flow interacts with the cells’ surface. Multiple jet inlets are introduced that enable the air flow to change its directions and pass through the dead air regions. A hybrid technique is also used in which a liquid jacket is added to each of the cells. The liquid within the jackets is in contact with the cells maximizing the contact surface area to improve heat transfer. Steady state computational fluid dynamic simulations are performed to study the effects of the passive and hybrid techniques added to the battery pack. The results indicate a substantial improvement in the temperature uniformity. The temperature difference of the hybrid battery pack reduces from 4.87 °C to 1.26 °C. Additionally, the temperature variance at the cell level reduces from 3.29 °C to 0.36 °C. This battery pack does not require moving parts and pumping power and it can achieve high levels of temperature uniformity.

A modified efficiency‐oriented optimal method for three‐phase interleaved LLC resonant converter in plug‐in hybrid electric vehicle battery chargers

Three-phase interleaved LLC resonant converters are preferably employed to realize high efficiency and high power density in the application of On-board Charger. The parameter design of LLC resonant converter with wide range output has always been rigorous and difficult. Compared with the common time-domain model, a high-accuracy time domain analysis is adopted to analyze the interaction between three phases in detail. This method improves the accuracy of the design results by adding the interaction analysis. According to the operation mode analysis, transformer's turn ratio, resonant inductor, magnetic inductor and resonant capacitor are optimized based on the design principle of minimizing the conduction loss. Finally, the modified efficiency-oriented optimal method of wide output range LLC resonant converter is proposed and its design results is validated by a 6.6 kW prototype. The efficiency of the design using proposed method is significantly improved than the results of the common time-domain model.

Drive circuitry of an electric vehicle enabling rapid heating of the battery pack at low temperatures.

SummaryHeating battery at low temperatures is fundamental to avoiding the range anxiety and the time-consuming charging associated with electric vehicles (EVs). One method for achieving fast and uniform battery heating is to polarize the cell under pulse currents. However, the on-board implementation of this method leads to an increase in the cost and size. Therefore, in this study, an adapted EV circuitry compatible with the existing one and an optimized operating condition are proposed to enable rapid battery heating. With this circuit, electricity transfer between the cells can be realized through a motor, leading to remarkably higher battery currents than those of the conventional circuit. The increase in the maximum heating currents (from 1.41C to 4C) resulted in a battery temperature rise of 8.6°C/min at low temperatures. This heating method exhibits low cost, high efficiency, and negligible effects on battery degradation, practical and promising on battery heating of EVs.

Effect of Petroleum Pitch-Coating on the Electrochemical Performance of Graphite As Anode Materials

Lithium ions batteries (LIBs) have become the most promising energy storage device in new energy field due to their potential utility as high-energy-density batteries for electric vehicles and hybrid electric vehicles. Graphite, which is the most widely commercialized anode material of LIBs, exhibits structural stability and excellent cycle characteristics. However, graphite has some problems to overcome. Due to the uneven SEI (Solid Electrolyte Interface) layer generated after the initial cycle, considerable irreversible capacity loss occurs. This results in electrode collapse and cycle instability especially in high-rate charging. Therefore, many researchers have been reported to improve the stability of graphite with carbon coating.In this study, electrochemical characteristics of artificial graphite coated with petroleum pitch were investigated as anode materials of lithium ion batteries. To improve the capacity and stability of graphite, it was coated with petroleum pitch(SP, 150, 200 and 250 ℃). The physical properties of prepared samples were analyzed by MALDI-TOF, TGA, XRD, SEM and TEM. The electrochemical performances of graphite composites as an anode were evaluated by initial charge/discharge, cycle, rate performance, cyclic voltammetry and electrochemical impedance spectroscopy (EIS) tests. The electrolyte used in the half cell was 1.0 M LiPF6 dissolved in organic solvents (EC:DEC=1:1 vol%).It was found that the pitch(SP 250 ℃) anode materials had excellent electrochemical characteristics: good initial efficiency (92.9%), discharge capacity (343 mAh/g), cycle stability (97%), and rate performance (84.1% in 10 C/0.1 C) than that of pristine graphite.

Development of the cycling life model of Ni-MH power batteries for hybrid electric vehicles based on real-world operating conditions

For the hybrid electric vehicle (HEV), accurate prediction of the remaining use life for the power batteries under actual operating conditions is of great significance to the battery power state of charge (SOC) estimation, as well as to the reliability and safety. However, there is little study available to evaluate the battery degradation behavior in real applications. Current battery degradation model is mostly established based on laboratory condition. In such case, charging/discharging scenarios are mostly constant across the battery cycle, and thus, they may be not a good representative of the working condition of the Ni-MH in real application where charging/discharging are frequently altered. Therefore, in this paper, the cycle life degradation characteristics of Ni-MH batteries for HEVs were studied, and an experienced model of cycle life is established based on the data from the real-world driving settings. The cycle life results indicated that the capacity loss is strongly impacted by the charge and discharge rate (C-rate), temperature, and depth of discharge (DOD). A large cycle test matrix is used to collect battery life data to build the model. The test matrix parameters include temperature (25 °C, 45 °C, 55 °C), DOD (0.5, 0.8, 1) and C-rate (1C, 2C, 5C). To verify the reliability of the life model applied to the HEV, the equivalent cycle life test verification of the real vehicle road spectrum was carried out. The test results show that the model can characterize the battery's decay process well.

Stochastic capacity loss and remaining useful life models for lithium-ion batteries in plug-in hybrid electric vehicles

This paper proposes and validates a stochastic prognostic model for capacity loss and remaining useful life (RUL) in lithium-ion pouch cells with graphite anodes and NMC–LMO cathodes. The model was developed using data from an experimental campaign which studied the effect of C-rate, minimum SOC, temperature, and charge-depleting usage on aging in plug-in hybrid electric vehicle (PHEV) batteries. The proposed algorithm estimates capacity loss and RUL as a function of resistance and operating conditions including charge sustaining/depleting use and temperature, and its stochastic nature is able to capture the variability of the data. The battery resistance is estimated using a particle filter developed for an experimentally validated equivalent circuit battery model. The particle filter is designed to perform combined estimation of State of Charge and internal resistance, which is used as an input to the stochastic capacity loss model. Finally, the stochastic model predicts the capacity loss with a root mean square error (RMSE) of less than 1% and RUL with an RMSE of 1.6 kAh, and can be integrated into on-board battery management systems in PHEV to monitor the health of lithium-ion batteries.

Development of status detection method of lithium-ion rechargeable battery for hybrid electric vehicles

In order to maximize the performance of lithium ion batteries, we have developed a new method for detecting the status of hybrid electric vehicle (HEV) batteries. The method obtains an accurate state of charge (SOC) by combining the SOC based on open circuit voltage (OCV) and the SOC based on current integration. In addition to that, our method has an auto-tuning function, which is realized by relatively simple processing, for the characteristic parameter of batteries. Our method can also obtain the state of health (SOH) by watching the tuned characteristic parameter. We perform simulation evaluations of our method with a battery model, and we confirm that the SOC error is less than 5% even if SOH set in the battery model and in our method are under mismatched condition. We also confirm that the SOH gradually converges to the true value and SOC error is improved by performing simulation evaluation repeatedly.