Constant Current And Constant Voltage Research Articles

Research on topology technology of integrated battery energy storage system with reconfigurable battery and converter

In traditional battery energy storage systems (BESS), batteries are usually connected in a simple series or parallel form, and separate converters and balancing modules are typically used for energy exchange between the battery and external sources, as well as for balancing energy between batteries. This paper proposes an integrated battery energy storage system (IBESS) with reconfigurable batteries and DC/DC converters, resulting in a more compact structure. The IBESS can reconfigure the connection of energy storage batteries based on the battery's status and external demand. The DC/DC converters can operate in different modes such as boost, buck, or buck-boost converters. The IBESS has five working modes: discharging mode, balancing mode, battery discharging and balancing mode, constant current and constant voltage (CCCV) charging mode and backup mode. To verify the feasibility of the proposed energy storage system, a model with four battery modules was built using MATLAB/SIMULINK, and the operation of all working modes was demonstrated. The simulation results verified the system's performance and reliability, demonstrating its flexibility and efficiency in different operating modes.

Electrochemistry-Based Diagnosis of Li Plating for Fast-Charging Li-Ion Batteries

Recent innovations in battery technologies have facilitated the development and widespread use of electric vehicles (EVs), by increasing the energy density of batteries while lowering their cost. Despite the rapid growth of the EV market, the long charging time of lithium-ion batteries (LIBs) remains as a major obstacle for expanding customer acceptance of EVs. Typically, graphite-based anodes in the state-of-the-art LIBs suffer from Li plating under fast-charging conditions, which causes severe performance degradations and early cell failure of batteries. To prevent the Li plating-induced failure, extensive research efforts have been devoted to developing diagnostic methods capable of detecting Li plating. The electrochemical analysis of Li plating enables non-destructive, in operando detection without complicated experimental procedures or special equipment.Herein, we present a non-destructive method for detecting Li plating during fast-charge cycling by analyzing current transients during the constant-voltage charging step, based on electrochemical battery models. Three-dimensional (3D) and pseudo-two-dimensional (P2D) battery models are employed to predict the electrochemical behavior of full cells under fast-charging conditions. 3D model enables the evaluation of local electrochemical properties, such as local reaction current densities and electrode potentials, which are largely affected by the microstructure of the electrode. Furthermore, P2D models are employed to investigate the effect of changes in microstructural properties (e.g., porosity and fraction of active surface of the graphite anode) on electrochemical behavior of full cells.For 3D modeling, the 3D Voronoi tessellation and Catmull-Clark algorithm are employed to construct the model geometry of graphite anodes. 3D modeling results predict that upon fast-charging, the charge-transfer potential on the top surface of graphite anode rapidly drops below 0 V vs. Li/Li+, triggering Li plating. To extract the electrochemical signals of Li plating, the fast-charging behaviors of full cells are investigated by using the P2D model with a partially reversible Li plating–stripping reaction. In specific, the constant-current and constant-voltage (CC-CV) charging process of the full cells with graphite anodes is simulated with Li plating-induced degradation modes; reduction of (i) interparticle pores, (ii) active surface area for Li intercalation reaction, and (iii) cyclable Li amount. Modeling results demonstrate that an inflection point appears in the current transient curve, and it shows a positive shift when the Li plating-induced degradation occurs. Electrochemical tests and microstructural analyses further confirm the validity of proposed electrochemical detection of Li plating. This study provides an effective strategy to design electrochemical methods for Li plating detection during fast-charging batteries based on electrochemistry-based models.

A Bayesian deep learning pipeline for lithium‐ion battery SOH estimation with uncertainty quantification

AbstractIn recent years, deep learning (DL) methods for state of health (SOH) estimation of lithium‐ion (Li‐ion) batteries have attracted great attention. However, most existing DL‐based methods for SOH estimation were designed using specific battery dataset. To gain better performance, the procedure can be labor‐intensive, involving designing intricate features and fine‐tuning complex DL model, which significantly limits the applications of these methods. Moreover, uncertainty quantification, that is how much uncertainty these DL‐based methods can have on their SOH estimation, cannot be addressed with only point estimation. To this end, this paper proposes a Bayesian DL pipeline for Li‐ion battery SOH estimation targeting at automatic feature extraction and uncertainty‐aware DL‐model developing for general application to batteries under different working conditions. The proposed pipeline is composed of three modules accounting for common feature extraction, automatic feature selection, and Bayesian neural network (BNN) model construction. Specifically, a frequently‐used feature set is designed using the voltage, current and time data of constant current and constant voltage (CC‐CV) charging mode, while the recursive feature elimination (RFE) with cross validation (RFECV) algorithm is used to automatically select features based on relevance. Based on the automatically selected features, DL model is automatically constructed without too much human intervention. The uncertainty of SOH estimation is quantified by BNN model using Monte Carlo (MC) dropout method, which is subsequently used to calculate the confidence of the estimation results. Four battery datasets, covering regular charging, fast charging, and second‐use applications, are used to demonstrate the performance of the proposed method. The proposed pipeline shows superior performance to state‐of‐art DL‐based methods in terms of application capability to different working conditions and uncertainty quantification for SOH estimation.

Adaptive control-based Isolated bi-directional converter for G2V& V2G charging with integration of the renewable energy source

In this research paper, Adaptive control-based Isolated bi-directional converter for modernized electric vehicle system is introduced with control on charge and discharge of the electric vehicle (EV) battery as per the reference value. The EV battery is operated in two modes, such as charge (Grid-to-Vehicle) mode and discharge (vehicle-to-grid) mode. In charging mode, constant current and constant voltage (CCCV) control is adopted with control on charging voltage and current. Whereas in discharging mode, constant current (CC) control is adopted for control on discharge current from battery into the grid. The grid is also interconnected to PV system for renewable energy power sharing. In both the control techniques, ANFIS is integrated for better performance of the battery during charge and discharge conditions. The ANFIS takes input from error generated by comparison of reference and measured value and produces the required duty ratio value. The training of the fuzzy structure is done using data generated from the PI controller input and output. The training uses hybrid algorithm for adapting the data points considered from the PI controller. The EV battery is charged using the conventional AC grid and the renewable energy source in G2V mode, and the EV battery and renewable energy sources are used to supply power to the AC load in the V2G mode, which reducing the load demand on the AC grid. The DC-Link voltage and power to the AC load are kept constant in both modes of operation by using a synchronous reference frame controlled VSC and an ANFIS controlled dual active full bridge converter. The incremental conductance MPPT algorithm is used to control the Photo Voltaic Array (PVA). The proposed work is implemented using MATLAB/Simulink and HIL performance of the proposal system is examined in the RT-LAB OP-5700 real time simulator environment.

Design of Modified Luo Converter for Electric Vehicle Battery Charger

Higher energy and battery efficiency are now major concerns for Electric Vehicle (EV) manufacturers and consumers. The main component of the two-stage EV on-board charger is the DC-DC converter. The phase displacement of full-bridge to operate the switch at either zero voltage or zero current in a power switch DC-DC converter, currently has issues such as voltage variation on the consequent side, which is secondary of the transformer, and it implies poor performances. Power Factor Correction (PFC) converters used in modern EV chargers achieve high performance and adequacy throughout charging. A modified luo converter is designed to achieve high efficiency in EV charging. A luo converter is a type of PFC that is commonly used as a converter of DC to DC with improved voltage regulation in the presence of rapidly changing line voltages. In this aimed work, a reformed separate Luo converter-based electric vehicle charger is developed. To suppress voltage oscillations, two devices which means switches and two clipping diodes are connected at the elementary side in the detachment of High Frequency Transformer (HFT). The Luo converter handles Discontinuous Conduction Mode (DCM) of operation, decreases control complexity, and keeps converter's output constant. In the feedback system, the Constant Current and Constant Voltage (CC-CV) mode technique is used in conjunction with the PI controller to improve competence and reduce transmission leakage. The proposed system's performance is evaluated by applying in MATLAB/SIMULINK software, and the outcomes are promising.

PSO-LSSVM-based Online SOC Estimation for Simulation Substation Battery

As the emergency power supply for a simulation substation, lead-acid batteries have a work pattern featuring non-continuous operation, which leads to capacity regeneration. However, the accurate estimation of battery state of charge (SOC), a measurement of the amount of energy available in a battery, remains a hard nut to crack because of the non-stationarity and randomness of battery capacity change. This paper has proposed a comprehensive method for lead-acid battery SOC estimation, which may aid in maintaining a reasonable charging schedule in a simulation substation and improving battery’s durability. Based on the battery work pattern, an improved Ampere-hour method is used to calculate the SOC during constant current and constant voltage (CC/CV) charging and discharging. In addition, the combined Particle Swarm Optimization (PSO) and Least Squares Support Vector Machine (LSSVM) model is used to estimate the SOC during non-CC discharging. Experimental results show that this method is workable in online SOC estimation of working batteries in a simulation substaion, with the maximum relative error standing at only 2.1% during the non-training period, indicating a high precision and wide applicability.

Charging Strategy Optimization at Low Temperatures for Li-Ion Batteries Based on Multi-Factor Coupling Aging Model

Lithium-ion batteries (LIBs) charging at low temperatures will easily accelerate the aging of LIBs and reduce the useful life. This paper applies advanced multi-factors coupling aging model and bi-objective particle swarm optimization (PSO) algorithm to derive suitable charging patterns for LIBs at low temperatures. Based on the results of orthogonal experiments, which consider the effects of charging rate, charging temperature and charging cut-off voltage on battery aging, the low-temperature capacity degradation model was established. Furthermore, two important yet competing charging objectives, including battery health and charging time, are taken into account simultaneously. These two conflicting charging objectives are traded off by solving a bi-objective optimization problem based on battery electrothermal and aging behavior. Combined with PSO algorithm, the optimal low-temperature charging strategy is obtained. As a result, the three-stage constant current and constant voltage (CC-CV) charging strategy is optimized to balance various combinations of charging objectives. Different tradeoffs are compared and analyzed based on the Pareto frontiers. The verification results show that the optimized three-stage CC-CV charging strategy can effectively offer feasible health-conscious charging with desirable tradeoffs among charging speed and battery health under low-temperature charging conditions.

Inductive power transfer system with constant current and constant voltage outputs for battery charging based on double‐channel T‐circuit

To ensure the safety and effectiveness of charging a battery, constant current and constant voltage (CC-CV) charging is widely used in inductive power transfer (IPT) systems. A double-channel T-circuit (DT) is proposed to obtain CC output or CV output by selecting different work modes with a simple feedback control for various power demands. With the merit of the proposed circuit, fewer components are employed compared to previous work with zero phase angle (ZPA) of inverter in the whole charging process. Besides, an IPT system using DT cascaded with LCC-S (DTLS) is proposed to improve design freedom of the charge current and charge voltage with the constraints of the magnetic coupler (MC) parameters for CC-CV charging. Finally, a prototype with 60 V/2 A output was built to verify the theoretical analysis. The experimental results show that the fluctuation of the charging current is less than 2% in CC mode, and that of charging voltage in CV mode is within 4% with the maximum efficiency up to 93.36% during the whole charging process.

A Novel Design Method of LCC-S Compensated Inductive Power Transfer System Combining Constant Current and Constant Voltage Mode via Frequency Switching

Inductive power transfer (IPT) is an attractive wireless power charging option in many applications such as electric vehicle biomedical devices and consumer electronics, etc. Constant current and constant voltage (CC-CV) charging profile is widely used for charging applications due to affecting the life and the reliability of the Li-ion battery. However, the IPT systems that can achieve both CC and CV modes with soft switching are not well studied. This paper presents an inductive power transfer system for wireless charging without a back-end converter, which achieves the required two-stage charging profile with high efficiency by keeping inverters’ soft switching operation. The characteristics of an LCC-S compensation topology have been investigated thoroughly. Two fixed resonant frequencies, whose analytical expressions have been derived, can be found to realize constant current output and constant voltage output respectively under zero-phase angle condition. Besides, an effective tuning method has been presented for zero voltage switching realization to reduce the switching loss. Moreover, a parameter design procedure has been summarized for the wireless charger with a simplified structure and high efficiency. Finally, the method is validated through experiments on a 3.5kW prototype realizing constant current and constant voltage outputs with a peak efficiency of 97.3%.

Optimal Hybrid Neuro-fuzzy Based Controller Using MOGA for Photovoltaic (PV) Battery Charging System

This paper proposes an optimal hybrid neuro-fuzzy/fuzzy controller based on maximum power point tracking (MPPT) technique and voltage regulation for photovoltaic lead-acid battery charging system through the constant current and constant voltage (CC-CV) charge, denoted by NFC-CC/FLC-CV. The parameter optimization of NFC and FLC, including rule selection, based on multi-objective genetic algorithm (MOGA) is applied to the NFC-CC design to improve the tracking accuracy while reducing complexity. By means of genetic optimization, the number of fuzzy rules can be greatly reduced by 50%. In addition, GA is applied to the FLC-CV design to increase voltage regulation (VR) accuracy. After satisfying the stability condition through the solutions determined by MOGA and GA, the performances of controllers under rapidly-changing weather are evaluated tradeoff by several creteria, including transient response, stabilized accuracy, charging time, and energy utilization and charging efficiency. As results, the proposed controller outperforms the other existing controllers with the fastest rise time without overshoot, the highest MPPT and VR accuracy with negligible oscillations, a 12-23% reduction in charging time, and an increase of 5-15% and 1-6% in energy utilization and charging efficiency. Furthermore, it provides superior results in terms of computational complexity by achieving the minimum number of multiplications and system parameters, and high reliability with the lowest Akaike information criterion (AIC).

Multistage CC-CV Charge Method for Li-Ion Battery

Charging the Li-ion battery with constant current and constant voltage (CC-CV) strategy at −10°C can only reach 48.47% of the normal capacity. To improve the poor charging characteristic at low temperature, the working principle of charging battery at low temperature is analyzed using electrochemical model and first-order RC equivalent circuit model; moreover, the multistage CC-CV strategy is proposed. In the proposed multistage CC-CV strategy, the charging current is decreased to extend the charging process when terminal voltage reaches the charging cut-off voltage. The charging results of multistage CC-CV strategy are obtained at 25°C, 0°C, and −10°C, compared with the results of CC-CV and two-stage CC-CC strategies. The comparison results show that, at the target temperatures, the charging capacities are increased with multistage CC-CV strategy and it is notable that the charging capacity can reach 85.32% of the nominal capacity at −10°C; also, the charging time is decreased.

Li-Ion Battery Pack Charging Process and Monitoring in Electric Vehicle

This paper presents the charging process procedure of Li-ion Battery pack for electric vehicle, which is implemented based on constant current and constant voltage (CC-CV) mode. All the informations regarding battery voltage level, state of charge (SOC) during charging and discharging processes, and battery temperature, is displayed on computer via battery management system (BMS). During the charging process, the BMS monitors the voltage balancing in Li-ion battery pack, as well as the cells voltage in each modules. The voltage difference between the highest voltage cell and the lowest voltage cell is very small, which validates the voltage stability and balance in battery pack during the charging and discharging processes.

Digital Control of Secondary Active Clamp Phase-Shifted Full-Bridge Converters

A DSP-based self-adaptive proportional-integral (PI) controller to control a DC-DC converter is proposed in this paper. The full-bridge topology is adopted here to obtain higher power output capability and higher conversion efficiency. The converter adopts the zero-voltage-switching (ZVS) technique to reduce the conduction losses. A parallel secondary active clamp circuit is added to deal with the voltage overshoot and ringing effect on the transformer’s secondary side. A self-adaptive PI controller is proposed to replace the traditional PI controller. Moreover, the designed converter adopts the constant-current and constant-voltage (CC-CV) output control strategy. The secondary active clamp mechanism is discussed in detail. The effectiveness of the proposed converter was experimentally verified by an IGBT-based 10kW prototype.

DSP-Based Probabilistic Fuzzy Neural Network Control for Li-Ion Battery Charger

A DSP-based probabilistic fuzzy neural network (PFNN) controller to control a two-stage ac-dc charger is pro- posed in this study. The charger is composed of an ac-dc boost converter with power factor correction and a phase-shift full- bridge dc-dc converter. Moreover, the designed charger adopts a constant-current and constant-voltage (CC-CV) charging strategy to charge lithium-ion battery packs. To improve the transient of voltage regulation during load variation, a PFNN controller is pro- posed to replace the traditional proportional-integral controller. Furthermore, the discontinuous charging voltage and current during the transition between the CC and CV charging modes can also be reduced significantly using the proposed PFNN controller. The network structure and the online learning algorithms of the PFNN controller are introduced in detail. In addition, the control performances of the proposed PFNN control system for CC-CV charging are evaluated by experimental results.

Design of Duty-Varied Voltage Pulse Charger for Improving Li-Ion Battery-Charging Response

In this paper, a duty-varied voltage pulse-charge strategy (DVVPCS), that can detect and dynamically track the suitable duty of the charge pulse, is proposed to improve the battery-charge performance. To assess the system performance, a prototype of the duty-varied voltage pulse charger (DVVPC) is designed and implemented. Comparing with the standard constant-current and constant-voltage (CC-CV) charge strategy, the charge speed of the proposed DVVPCS is improved by about 14%, while the proposed DVVPCS is improved by about 5% in comparison with the conventional duty-fixed voltage pulse-charge strategy (DFVPCS). The charge efficiency of the proposed DVVPC has been improved by about 3.4% as compared with that of the general CC-CV. In comparison with conventional DFVPCS with D = 50%, the charge efficiency of the proposed DVVPCS is improved by about 1.5%. The results indicate that the DVVPCS can actually provide pulse with suitable duty to charge the battery, and the charge performance is improved.

Development of First Principles Capacity Fade Model for Li-Ion Cells

A first principles-based model has been developed to simulate the capacity fade of Li-ion batteries. Incorporation of a continuous occurrence of the solvent reduction reaction during constant current and constant voltage (CC-CV) charging explains the capacity fade of the battery. The effect of parameters such as end of charge voltage and depth of discharge, the film resistance, the exchange current density, and the over voltage of the parasitic reaction on the capacity fade and battery performance were studied qualitatively. The parameters that were updated for every cycle as a result of the side reaction were state-of-charge of the electrode materials and the film resistance, both estimated at the end of CC-CV charging. The effect of rate of solvent reduction reaction and the conductivity of the film formed were also studied. © 2004 The Electrochemical Society. All rights reserved.

Collaborative investigation on charging electic-vehicle battery systems for night-time load levelling by Japanese electric power companies

In 1995, ten Japanese electric power companies and CRIEPI started a three-year collaborative investigation of battery systems for electric vehicles (EVs). In the first year, the charging procedure for valve-regulated lead/acid (VRLA) batteries connected in series in EVs has been evaluated for both night-time load levelling and prolonging the cycle life. An EV battery system with VRLA batteries can be charged by both constant current and constant current (CC-CC) and constant current and constant voltage (CC-CV) in less than 8 h under night-time conditions. The charging method with CC-CC prolongs the cycle life further than that with CC-CV. Excess charging capacity on the part of CV in CC-CV charging degrades the positive electrode through softening of the active material. A higher rate of the first current in CC-CC charging prolongs the cycle life by suppressing the softening of the positive electrode due to active-material particle growth. On the other hand, control of the uniform environment in battery boxes during the charging with CC-CC and CC-CV is very important in order to prolong the cycle life. This is because cooled batteries tend to have insufficient charge capacity due to their greater energy consumption for the electrolysis of water than uncooled ones.