Lithium-ion Battery Bank Research Articles

A novel approach to modeling and experimenting a solar-fed H6 configuration for battery swapping stations in rural and commercial areas using a dual phase CLLC DC–DC resonant converter

In order to further the use of clean energy, the transition from internal combustion engine (ICE) vehicles to electric vehicles (EVs) was initiated globally. In the coming days, there will be a need for more EV charging stations in rural and commercial areas. The installation of new charging infrastructure for different vehicles with different voltage specifications in order to charge batteries are expensive with limited availability. Also fast charging is not possible in rural areas. To overcome this issue, the battery swapping station is a good option. In this paper, a new solar-powered dual-phase CLLC DC–DC resonant converter is proposed to test battery swapping. An equivalent circuit has been derived analytically, and the optimal design of the magnetic components for the proposed converter has been derived. Simulation has been carried out for the proposed system. The proposed system was tested with a prototype set-up of a 100 W lithium-ion battery bank of equal and unequal voltage levels in an open-loop condition using Analog Discovery-2. Introducing the H6 concept in the proposed converter has the features of low stress across switches, use of higher dc grid voltage, low switching losses due to the dual phase resonant compensation network, and a multi-port isolated output system. Apart from battery swapping applications it can be utilized for Energy Storage Solution [ESS].

Comparative analysis of different FOPI approximations and number of terms used on simulations of a battery-powered, field-oriented induction motor based electric vehicle traction system

Because of their enhanced performance, the fractional order proportional-integral (FOPI) controllers are becoming an appealing choice for controlling induction motor speed. To implement FOPI controllers, several fractional order integral approximations are available in the literature. The approximation used, and the order of approximation affects the speed tracking, transient response, and induction motor power consumption. This further affects the energy consumption analysis if simulations are conducted based on such approximations. In this paper an electric vehicle (EV) traction system is simulated to investigate the effect of such approximations on the simulations of a battery powered, induction motor driven EV system. The system consists of an indirect field-oriented induction motor, a lithium-ion battery bank, and a three-phase inverter. This work presents a quantitative analysis of the performance of FOPI controllers using different approximations, and order of approximations is presented. The controllers are evaluated based on speed tracking, transient response, computational time, and power consumption. Both step functions and standard drive cycles are used as the speed reference signal to evaluate the effects of using different approximations and different orders of approximation, when different references are used. This work establishes a reference set of simulations that can be used to infer the amount of error in battery state of charge, and state of health analysis conducted on such an EV system, when dealing with FOPI controllers under different approximations and related settings.

Economic model predictive control for energy management of a microgrid connected to the main electrical grid

Electric microgrids have become an interesting tool to facilitate the inclusion of renewable energies. Its architecture and control system plays a fundamental role in the implementation of these systems. This paper proposes a control strategy for the management of energy resources in a residential microgrid. The system is made up of a set of solar panels as renewable resource, a storage system formed by a lithium-ion battery bank and a consumption profile according to a residence. The microgrid will be connected to the main electrical grid and the proposed management strategy consists in the implementation of a suitable Economic Model Predictive Control, where it considers the costs of use for the different components of the microgrid, thus contemplating the participation of the system as an active agent in the electricity market. Simulations were carried out with different scenarios of available resources and prediction times. In all cases, the objectives fulfilling by satisfying the restrictions operational and technical imposed on the system.

Battery Energy Management Techniques for an Electric Vehicle Traction System

This paper presents two battery energy management (BEM) techniques for an electric vehicle (EV) traction system which incorporates an indirect field-oriented (IFO) induction motor (IM) drive system. The main objective of the proposed BEM techniques is to regulate the IM’s speed while minimizing the lithium-ion (Li-ion) battery bank state of charge (SOC) reduction and state of health (SOH) degradation. In contrast to most of the existing work, the proposed BEM techniques operate without any prior knowledge of driving profiles or road information. The first BEM technique incorporates two cascaded fuzzy logic controllers (CSFLC). In CSFLC, the first fuzzy logic controller (FLC) generates the reference current signal for regulating the motor speed, while the second FLC generates a variable gain that limits the current signal variation based on the battery SOC. The second BEM technique is based on model predictive control (MPC) which generates the current signal for the speed regulation. However, this work introduces a new way of tuning the MPC input weight using battery information. It features a fuzzy tuned model predictive controller (FMPC), where an FLC adjusts the input weight in the MPC objective function such that the battery SOC is considered while generating the command current signal. Furthermore, this work utilizes a model-in-loop strategy comprising a Chen and Mora (CM) battery model and the experimentally obtained battery bank power consumption to estimate the increase in battery bank runtime and lifetime. A real-time implementation is carried out on a prototype EV traction system using the New European Drive Cycle (NEDC) and the Supplemental Federal Test Procedure (US06) drive cycles. The experimental results validate that the proposed CSFLC and FMPC BEM techniques exhibit a lower reduction in the battery SOC and SOH degradation, thus prolonging the battery bank runtime and lifetime as compared to the conventional FLC and MPC speed regulators. Further experimentation demonstrates the superiority of the FMPC technique over the CSFLC technique due to the lesser computational burden and higher average energy saving.

Fault Ride-Through Power Electronic Topologies for Hybrid Energy Storage Systems

This work presents a fault ride-through control scheme for a non-isolated power topology used in a hybrid energy storage system designed for DC microgrids. The hybrid system is formed by a lithium-ion battery bank and a supercapacitor module, both coordinated to achieve a high-energy and high-power combined storage system. This hybrid system is connected to a DC bus that manages the power flow of the microgrid. The power topology under consideration is based on the buck-boost bidirectional converter, and it is controlled through a bespoke modulation scheme to obtain low losses at nominal operation. The operation of the proposed control scheme during a DC bus short-circuit failure is shown, as well as a modification to the standard control to achieve fault ride-through capability once the fault is over. The proposed control provides a protection to the energy storage systems and the converter itself during the DC bus short-circuit fault. The operation of the converter is developed theoretically, and it has been verified through both simulations and experimental validation on a built prototype.

Model Predictive Control-Based Coordinated Control Algorithm with a Hybrid Energy Storage System to Smooth Wind Power Fluctuations

Stochastically fluctuating wind power has an escalating impact on the stability of power grid operations. To smooth out short- and long-term fluctuations, this paper presents a coordinated control algorithm using model predictive control (MPC) to manage a hybrid energy storage system (HESS) consisting of ultra-capacitor (UC) and lithium-ion battery (LB) banks. In the HESS-computing period, the algorithm minimizes HESS operating costs in the subsequent prediction horizon by optimizing the time constant of a flexible first-delay filter (FDF) to obtain the UC power output. In the LB-computing period, the algorithm keeps the optimal time constant of the FDF from the previous period to directly obtain the power output of the UC bank to minimize the power output of the LB bank in the next prediction horizon. A relaxation technique is deployed when the problem is unsolvable. Thus, the fluctuation mitigation requirements are fulfilled with a large probability even in extreme conditions. A state-of-charge (SOC) feedback control strategy is proposed to regulate the SOC of the HESS within its proper range. Case studies and quantitative comparisons demonstrate that the proposed MPC-based algorithm uses a lower power rating and storage capacity than other conventional algorithms to satisfy one-minute and 30-min fluctuation mitigation requirements (FMR).

Coordinated Power Management for Variable Speed Diesel Generator and Lithium-ion Battery Hybrid System

This paper presents coordinated operation of power management strategies for a hybrid system. This hybrid system is modeled based on dynamic variation of load power and its effective distribution strategy. The proposed hybrid system consists of variable speed diesel generator (VSDG) and lithium-ion battery which is able to supply electric power for Power, Water and Communication (PWC) economically and efficiently in rural areas. The variation of power demand in PWC load is highlighted in load profile. The total PWC load is effectively shared by two VSDGs and one Lithium-Ion battery bank. The use of advanced VSDG helps hybrid system to reduce fuel consumption as its speed varies with load demand. The proposed segmentation of high frequency and low frequency components of load currents and their assignation to suitable source helps to reduce the transients during load variations. Also, one of the generators will be switched off when the total power demand goes below specified level and hence significant fuel savings can be achieved. The execution of proposed system is assessed through MATLAB/Simulink model and its validation by experimental test bench.

Performance and Cost Analysis of Lithium-Ion Battery for Powering Off-Grid Telecoms Base Stations in Africa

Most African remote telecoms base stations are powered from diesel generators, however, these generators are losing attractiveness due to their less reliability in addition to high operational and maintenance costs. Over 65% of the loss of telecom services observed in remote areas are caused by outages resulting from diverse types of failures that these generators can suffer, on top of their impacts on the environment. As alternative, off-grid renewable energy systems are often employed in place of diesel generators due to their capability to provide reliable electricity at an acceptable cost. This study proposes an off-grid system based on PV generators and backup energy storage consisting of lithium-ion batteries as an extended solution for powering remote telecom base stations in Africa. Modelling and simulation is performed using Matlab/Simulink environment. The findings showed better characteristics of lithium-ion battery bank as compared to lead-acid unit; lithium-ion battery bank displayed higher initial current and voltage over lead-acid battery bank. Moreover, when, both battery banks reached 50 % of their state of charge, lithium-ion bank current was still higher than that of lead-acid bank. In the same vein, lithium-ion battery bank presented a slower discharge time than lead-acid battery bank on top higher values at 50 % and 70% state of charges. Lastly, the state of charge of the lead-acid battery at the end of the simulation was 50 %, while that of the lithium-ion battery bank was around 60 %.

Sizing an Energy System for Hybrid Li-Ion Battery-Supercapacitor RTG Cranes Based on State Machine Energy Controller

Ports and container terminals play an important role in the global logistics system. Handling containers inside container terminals and rail terminals are mostly carried out by rubber tire gantry (RTG) cranes. These cranes have quite different power profile compared to hybrid vehicles. They have a broad power demand, varying from 10kW to 350kW, 170kW regenerating power, and a maximum of 30kW auxiliary power. The high peak demand due to the acceleration of hoist drivetrain determines the prime mover (diesel generator) capacity. This capacity is highly over-rated when comparing with crane's average power demand. Such power profiles having high peak power to average power ratio can be supplied through hybrid systems which can downsize the diesel generator, improve fuel efficiency, reduce CO 2 emissions, and reduce maintenance cost. In this study, a hybrid energy source is presented for an RTG crane. The hybrid energy source comprises a Lithium-ion battery bank, supercapacitor (SC) bank connected to the DC-link through bi-directional DC/DC converters, and a downsized variable speed diesel generator (VSDG) connected to the DC-link through an active rectifier. The narrowband operation of the battery bank helps to increase the healthy life of the battery system reducing risk due to unhealthy conditions during faults and abnormal situations. In this paper, the sizing of a hybrid energy system controlled by a state machine controller is presented. Unlike traditional optimization-based sizing techniques, unique features of demand profile, operating environment, system redundancy, backup operation, readily available components, and specific features of state machine controller were highly considered which differentiate the method of sizing from others.

Predictive control model to manage power flow on a hybrid wind‐photovoltaic and diesel microgeneration power plant with additional storage capacity

This study proposes and evaluates a predictive control model for the management of the power flow in a hybrid microgeneration power plant with additional storage capacity. The plant integrates a photovoltaic array, a wind turbine, a diesel generator, and a lithium ion battery bank. One objective of the proposed predictive control model is to maximise the use of power from renewable resources looking for the weather predictions and thus minimise the use of fossil power from the diesel generator and corresponding CO 2 emissions. Another aim is to maximise the duration of lithium ion batteries, since extending their lifetime is crucial for the system's economic viability, and since battery disposal brings environmental concerns as well. A numerical evaluation is performed about the evolution of power dispatch decisions and of the batteries state of charge, depending on the available power storage capacity. Model predictive control proves to be a suitable strategy in this system.

Performance and power quality improvement based on DC-bus voltage regulation of a stand-alone hybrid energy system

This paper proposes an improved standalone configuration based on hybrid wind-PV with Lithium-ion battery bank combined with a Shunt Active Power Filter (SAPF). The hybrid system is controlled to produce the active power and to supply the load by a good power quality. The main idea of this novel configuration is to control the SAPF only to compensate the harmonic currents. In fact, the SAPF DC-side voltage and the PV system are directly connected to the common DC-bus of the hybrid system, which is regulated by the batteries through a buck-boost converter (BBC). Due to its regulation through a large Battery Energy Storage System (BESS), good dynamic response of the DC voltage is obtained, during a sudden variation in nonlinear load. Hence, the SAPF capabilities of harmonic filtering are enhanced. In addition, the proposed system is controlled to operate at the maximum power point under abrupt conditions, and to meet the load demand and maintain the output voltage and frequency at their desired values despite changes in load conditions. Finally, the SAPF performances are demonstrated through a comparison with a conventional configuration of the SAPF on various indices.

Control of a Hybrid AC/DC Microgrid Involving Energy Storage and Pulsed Loads

This paper presents a real-time coordinated control of the hybrid ac/dc microgrids involving energy storage and pulsed loads. Grid-isolated hybrid microgrid applications require special considerations due to the intermittent generation, online energy storage control, and pulsed loads. In this study, we introduce a comprehensive frequency and voltage control scheme for a hybrid ac/dc microgrid consisting of a synchronous generator, solar generation emulator, and bidirectional (ac/dc and dc/dc) converters. A bidirectional controlled ac/dc converter with an active and reactive power decoupling technique is used to link the ac bus with the dc bus, while regulating the system voltage and frequency. A dc/dc boost converter with a maximum power point tracking function is implemented to maximize the intermittent energy generation from solar generators. Current-controlled bidirectional dc/dc converters are applied to connect each lithium-ion battery bank to the dc bus. Lithium-ion battery banks act as energy storage devices that serve to increase the system resiliency by absorbing or injecting power. Experimental results are presented for verification of the introduced hybrid ac/dc power flow control scheme.

Capacity fade-based energy management for lithium-ion batteries used in PV systems

Battery storage has been widely used in renewable energy systems. Due to the high cost and limited life span of batteries, effective energy management is normally needed to optimize the battery usage. This paper proposes an online energy management (OEM) for a lithium-ion battery bank used in PV-based systems to meet the load demand. An electrical model and a capacity fade model of batteries, which have been experimentally calibrated, are combined and incorporated in the online energy management. By considering the different status of individual batteries in the battery bank, the proposed OEM aims to minimize the total capacity fade of the battery bank, as well as to economize the cost of using energy. The performance of the proposed OEM is tested and compared with a baseline method under three different scenarios using field-collected PV generation data, load demand data and the real-time uniform Singapore energy price. The proposed OEM shows significant advantages over the baseline method in terms of lower cost of using energy as well as smaller battery capacity fade.

多数枚のアルミニウム薄板の電磁圧接と衝突時間測定

A lithium ion battery bank used for electric vehicles is composed of many cells and current-collector tubs, and a large current passes through the tubs from the bank and flow to a motor. Moreover, a joining method for multi-stacked aluminum sheets is required. In this paper, we present a magnetic pulse welding method for five aluminum sheets with four gaps and a measurement method for four collision time signals. The four signals are simultaneously measured with two oscilloscopes. The five sheets used are of same thickness. An experiment is performed on 0.3, 0.5, 0.8 and 1.0mm thickness respectively. The first sheet on a plate coil experiences only an electromagnetic force, but the second sheet on the coil experiences both an electromagnetic force and an impact force by collision with the first sheet. Therefore, the time it takes for the second sheet to collide with the next sheet is always shorter than that for the first sheet. The five aluminum sheets were seam-welded along narrow middle of the coil. In a shearing tension test, five seam-welded sheets of 0.5mm thickness obtained at 3.5 kJ did not come off on four joined interfaces corresponding to the four gaps, but fractured in the five sheets. When all collisions generated in the four gaps are finished within a first wave of electromagnetic force, the five sheets may be strongly joined.

Wavelet-Based Capacity Configuration and Coordinated Control of Hybrid Energy Storage System for Smoothing Out Wind Power Fluctuations

Stochastically fluctuating wind power has a negative impact on power grid operations. This paper presents a wind power filtering approach to mitigate short- and long-term fluctuations using a hybrid energy storage system (HESS), and a novel wavelet-based capacity configuration algorithm to properly size the HESS. A frequency distribution allocates wind power fluctuations to the different HESS components to more easily satisfy 1-min and 30-min fluctuation mitigation requirements (FMR). An ultra-capacitor bank (UC) mitigates short-term fluctuations. In the HESS, and a lithium-ion battery bank (LB) minimizes long-term fluctuations. This paper also proposes a novel online-wavelet based coordination control scheme for the HESS, consisting of primary filtering (PF) and secondary filtering (SF) stages. The PF stage obtains a combined power output that fully satisfies the FMRs, while the SF stage provides additional smoothing of the wind power output fluctuations after the PF stage. A remaining energy level (REL) feedback control maintains the REL of the battery bank within its proper range. Case studies demonstrate that the proposed wavelet-based algorithm is more efficient than other published algorithms, and needs a lower energy storage capacity to satisfy 1-min and 30-min FMRs.