Optimal Charging Pattern Research Articles

Designing and Prototyping of Lithium-Ion Charging System Using Multi-Step Constant Current Method

The need for electrical energy means batteries have a critical role in technological developments in the future. One of the most advanced types of batteries is the lithium-ion battery. The conventional charging system has the disadvantage of taking a relatively long time, so the battery temperature is high. Therefore, a charging method that can shorten the charging time and extend battery life is needed. Some contributions of the paper are the design and prototype of a buck-boost converter for dual-mode lithium-ion battery charging (buck and boost mode) and the implementation of the Multi-Step Constant Current Method (MSCC) algorithm with an optimal charging pattern (OPT) to perform fast charging under voltage, current limit, and temperature monitoring. The test results showed that the proposed charging system prototype has an accuracy of 99.93% for the voltage sensor and 98.86% for the current sensor, whereas the precision of voltage and current sensors are 98.60% and 99.34%, respectively. The proposed method took 45 min to charge the 2-series (2S) and 4-series (4S) batteries. Compared to the CCCV method, the charging time of the MSCC method was 18.18% faster. In terms of battery temperature, MSCC had a lower peak temperature compared to CCCV by 1.5% and 1.25% for 2S and 4S, respectively.

Energy management of Plug-In Hybrid Electric Vehicles in renewable-based energy hubs

Proliferation of Plug-in Hybrid Electric Vehicles (PHEVs) and integration of various distributed generation (DG) technologies have been recognized to play an undeniable role in modern power systems of the future. In order to effectively model the interactions of these two technologies, this paper develops a multi-criteria framework to coordinate the charging behaviors of PHEVs within an energy hub platform. In this regard, the desirable charging profiles from the viewpoint of both PHEV owners and hub manager are first captured and reported to the PHEVs Coordinator Entity (PCE). The PCE, then, runs an optimization framework in which several criteria including the PHEV owners’ convenience, energy hub’s profit, and the technical performance of the distribution grid are all taken into account as a multi-criteria optimization framework resulting in the PHEVs’ optimal charging patterns. The proposed strategy is applied to the modified IEEE 34-node test system and the results demonstrate the applicability and efficiency of the proposed framework.

Coupled electromagnetic-thermal analysis of roadway inductive power transfer pads within a model pavement

Inductive Power Transfer (IPT) technology is a promising solution for wireless charging of Electric Vehicles (EVs). Given the expected uptake of IPT technology for both stationary and in motion in-road charging, many technical challenges regarding the electromagnetic field and thermal aspects need to be overcome to generate cost-effective and reliable solutions. One particular design constraint of in-road IPT systems is the occurrence of local increases in temperature during operation due to power losses in the wireless charging pads. In this paper, safe operating conditions of an enclosed wireless power transfer pad within a pavement model were identified. This aspect has been studied less rigorously compared with the electromagnetic design. This paper presents a numerical thermal analysis of a double-D (DD) prototype IPT primary pad based on two possible configurations; flush-mounted or buried, within a model pavement. A coupled electromagnetic-thermal simulation has been developed to aid in the development of thermally robust in-road IPT systems. In order to validate the proposed two-way coupled electromagnetic-thermal Finite Element (FE) simulations, experiments were performed to capture the evolving thermal field within an IPT primary pad under continuous and periodic duty cycles. This method made possible analysis of the heating patterns and so the identification of internal hotspots within an IPT pad in a roading structure. A thermal camera was used to provide detailed surface temperature distributions, while suitable application of non-metallic Fiber Bragg Grating (FBG) sensing technology enabled a robust technique to measure temperatures within the intense magnetic fields of a high frequency wireless power transfer system to be developed. Comparisons at steady state of the pavement surface temperature distribution, as well as point measurements with the pad and sand, demonstrate good accuracy. The maximum steady state surface temperature occurs at the centre of the sand surface where the IPT pad is placed and is approximately 87 °C and 100 °C for buried and flush-mounted pads, respectively. Moreover, for a 2/3 duty cycle loading, the maximum temperature of the pad tended to an average of approximately 76 °C, while at constant operation the average temperature is 105 °C. Therefore, a 5 min cooling period significantly reduced operating temperatures within the studied model IPT system. In the future, the methodologies proposed in this paper can also be used to improve the design of higher power IPT pads by identifying hotspots and maximum thermal stresses and determination of optimal charging patterns for heat dissipation.

An Electro-Thermal Model based fast optimal charging strategy for Li-ion batteries

<abstract> <p>This paper utilizes an integrated electro-thermal model of a lithium-ion battery to search for an optimal multistage constant current charge pattern that will minimize the total charging time of the battery, while restricting its temperature rise in each stage within safe limits. The model consists of two interlinked components, an electrical equivalent circuit model to continuously predict the battery's terminal voltage and a thermal model to continuously predict its temperature rise as charging progresses. The proposed optimization algorithm is based on a novel stepwise single-variable search technique that is very easy to implement and converges quickly. The results of our extensive simulation studies clearly indicate that the proposed charging strategy offers a fast, safe and easy-to-implement alternative to many of the existing computationally intensive optimal charging strategies.</p> </abstract>

Searching for the optimal current pattern based on grey wolf optimizer and equivalent circuit model of Li-ion batteries

In this study, a novel method is proposed to search for the optimal charging pattern (OCP) of the five stage constant current charging method. Firstly, a detailed equivalent circuit model of the lithium-ion battery obtained by Electrochemical Impedance Spectroscopy analysis is utilized to derive the mathematical expression of the charging time and the charging loss of the battery. Next, the grey wolf optimization method is utilized to find the optimal charging pattern which simultaneously takes the charging time and charging loss into account. According to the experimental results, the obtained OCP has the lowest temperature rise and the best charging efficiency. Compared with the conventional constant current- constant voltage charging technique with 1C charging current, the charging time, maximum temperature rise, average temperature rise, and charging efficiency are improved by 5.33%, 25.99%, 19.59%, and 0.48%, respectively. Comparing with the result obtained by optimization method which only takes the charging time into account, the maximum temperature rise, average temperature rise, and charging efficiency are improved by 12.54%, 5.74% and 0.21%, respectively. In addition, cycling results also show that the life cycle can be improved by 79.6% and 40.2% compared with the CC-CV charging method and the optimization result obtained by considering only the charging time.

Optimization of Variable-Current Charging Strategy Based on SOC Segmentation for Li-ion Battery

This paper presents a variable-current charging strategy of Li-ion batteries. Since the battery characteristics vary with state of charge (SOC), it is more reasonable to divide the charging process based on SOC than on cut off voltage. We find an optimal charging pattern of the proposed strategy by Non-dominated Sorting Genetic Algorithm-III (NSGA-III). The Second-order Thevenin model of battery is established to simulate the charging process. Verification experiments are performed and results show that the obtained charging pattern has a temperature and loss reduction of 2.9 °C and 0.5% compared with constant current-constant voltage (CC-CV) strategy under the same charging time and capacity.

Optimization of multi-stage constant current charging pattern based on Taguchi method for Li-Ion battery

Due to the complexity of characteristics, the charging performance of Li-ion batteries needs to be further improved. In this paper, Taguchi method is employed to search an optimal charging pattern for 5-stage constant-current charging strategy. The charging capacity, efficiency and time are analyzed as quality functions simultaneously, and the influences of charging currents at each stage on each quality function are revealed. This universal method provides a reasonable basis for the selection of the optimal currents. By reasonably updating the currents at each stage, a broader range is searched to make experimental results more representative. Compared with the constant current- constant voltage method, the obtained charging pattern improves the charging efficiency by 0.6–0.9%, and the temperature rise of the battery is reduced by about 2 °C. Compared with the charging pattern obtained by optimizing the charging time and capacity, the charging pattern obtained in this paper improved the charging efficiency by 2.8%, the temperature rise is reduced by 9.3 °C, and the charging capacity is basically the same.

Taguchi-based PSO for searching an optimal four-stage charge pattern of Li-ion batteries

Abstract This study utilizes a Taguchi-based particle swarm optimization algorithm to search an optimal four-stage constant current charge pattern for delivering the maximum capacity to provide long runtimes within the shortest charging time. The goal is to maximize the cost function for the applied charge pattern based on the charging time and discharge capacity ratio that both share the same weight. The discharge capacity ratio is defined as the total capacity of a cell discharged at a constant current of 0.3 C using the four-stage constant current charging strategy until reaching the preset voltage of 3.0 V to the one employs the constant current constant voltage charging method. The charging time is the overall charging duration of the 4SCC charging process. Sanyo UR14500P batteries in the cylindrical shape with a nominal voltage of 3.7 V and a rated capacity of 840 mAh are tested. In the tests, the optimal 4SCC sequence of 1.262 C, 1.082 C, 0.662 C and 0.258 C is allowed to charge the battery up to 94.7% of the nominal capacity for 67 min, and the constant current constant voltage charging arrangement of 0.7 C to 4.2 V and the cut-off of 0.05 C are used to charge the battery up to 99.5% of the nominal capacity in 119 min.

Unified energy management and load control in building equipped with wind-solar-battery incorporating electric and hydrogen vehicles under both connected to the grid and islanding modes

This paper presents a unified model for home energy management. The proposed model optimizes the cogeneration of wind, solar, and battery storage units. The introduced tool considers electric and hydrogen vehicles and provides optimal charging pattern for them. The water electrolyze is also modeled to produced breathable oxygen and hydrogen from water. As well, the load modeling options such as adjustable and interruptible loads are included in the planning in order to increase the flexibility and adeptness of the proposed energy management system. The uncertainties of wind and solar powers are included resulting in a stochastic programming. The proposed stochastic optimization problem is mathematically expressed as a mixed integer linear programming and solved by GAMS software. The problem minimizes cost of energy consumption in the building subject to the operational constraints of wind unit, solar panel, battery system, loads, electric-hydrogen vehicles, and electricity grid. The proposed test building is studied under two states including connected to the electrical grid and disconnected from the gird (i.e., islanding mode or NetZero energy home). The impacts of the proposed planning on the environmental pollution are also considered and simulated. The results verify that the proposed strategy can successfully utilize wind-solar-battery units to supply the load, charging the electric-hydrogen vehicles, and reduction of the pollution. As well, it is demonstrated that the operation of the home under islanding mode is completely different from the connected state.

Optimal Charge Pattern for the High-Performance Multistage Constant Current Charge Method for the Li-Ion Batteries

In this paper, a method is introduced to find out the optimal charge pattern (OCP) of the multistage constant current (MSCC) charge method based on the equivalent circuit model of a Li-ion battery. Unlike the conventional methods, the proposed one does not require several kinds of time-consuming and labor-intensive experiments. The OCP can be simply calculated by the developed equations with the results obtained by a simple experiment. The validity of the proposed method has been verified through the experimental results and it shows that the charge time and the charge energy can be reduced by 12% and 1.8%, respectively, and the charge efficiency of a Li-ion battery can be improved by 0.54% as compared to the conventional constant current-constant voltage (CC-CV) method. A lower temperature rise during the charge can be regarded as an additional advantage of the proposed method.

Multi-objective optimization of charging patterns for lithium-ion battery management

Lithium-ion (Li-ion) battery charging is a crucial issue in energy management of electric vehicles. Developing suitable charging patterns, while taking into account of various contradictory objectives and constraints is a key but challenging topic in battery management. This paper develops a model based strategy that optimizes the charging patterns while considers various key parameters such as the charging speed, energy conversion efficiency as well as temperature variations. To achieve this, a battery model coupling both the electric and thermal characteristics is first introduced. Three key but conflicting objectives, including the charging time, energy loss and temperature rise especially for internal temperature, are formulated. Then, multi-objective biogeography-based optimization (M-BBO) approaches are employed to search the optimal charging patterns and to balance various objectives with different combinations. Optimization results of four M-BBO approaches are compared, and the Pareto fronts for battery charging with various dual-objectives and triple-objectives are analysed in detail. Experimental results confirm that the developed strategy can offer feasible charging patterns and achieve a desirable trade-off among charging speed, energy conversion efficiency and temperature variations. The Pareto fronts obtained by this strategy can be adopted as references to adjust charging pattern to further satisfy various requirements in different charging applications.

Modeling of battery life optimal charging strategies based on empirical mobility data

Abstract Battery electric vehicles (EVs) have a more limited range and longer refueling, i. e. charging times accompanied by battery aging as conventional vehicles. Initial field studies about the behavior of EV users also have identified the presence of range anxiety, which is expressed by frequent recharging. Battery aging is a non-linear process with numerous interactions, but generally pronounced around higher state of charge (SoC) levels. Therefore, range anxiety potentially provokes elevated battery degradation due to the resulting operating conditions. Based on 2966 empirical driving profiles, I analyze different user groups as well as the effect of different charging strategies in a simulation-based analysis. In comparison to charging strategies, for instance as fast as possible (AFAP) charging or critical SoC charging (such that the next trip is feasible), I calculate the degradation optimal charging pattern based on a realistic battery cell aging model. The model is derived from accelerated aging tests of Li-NMC 18650 cells, but can be adjusted to individual degradation parameters, in order to account for different battery chemistries. Preliminary results show that degradation can be reduced by up to 46% by the optimized charging strategy as compared to AFAP or critical SoC charging.

A PSO-Based Fuzzy-Controlled Searching for the Optimal Charge Pattern of Li-Ion Batteries

This paper proposes a searching strategy based on particle swarm optimization, combined with a fuzzy-deduced fitness evaluator (FDFE), to find the optimal multistage charging pattern that delivers the most discharged capacity within the shortest charging time (CT). The objective function of the optimization problem is to maximize the cost effectiveness for the applied charging pattern based on the CT and normalized discharged capacity (NDC). Therefore, this paper proposes an FDFE to combine CT and NDC into a unified cost function to properly evaluate the multiple performance characteristics index in the charge problem. The experimental results show that the obtained pattern is capable of charging the batteries to over 88% capacity within 51 min. Compared with the conventional constant current–constant voltage method, the CT, the obtained life cycle, and the charging efficiency of the lithium-ion (Li-ion) battery for the devised approach are improved by approximately 56.8%, 21%, and 0.4%, respectively. The presented charging approach is suitable for the increasingly applications, in which the batteries are “sealed” inside the products to extend the life span.

Optimized Probabilistic PHEVs Demand Management in the Context of Energy Hubs

This paper develops a new framework to coordinate the charging process of plug-in hybrid electric vehicles (PHEVs) in the context of energy hubs. Attempts are focused not only on the impact evaluation of PHEVs on the system technical performance, but also customers' preferences on the charging patterns. PHEVs coordinator agent (PCA) is proposed to run a multiobjective optimization (MO) framework for the optimal charging patterns of PHEVs from the vehicle owners' and system operator's viewpoint. Wind energy utilization for PHEVs charging, energy costs at the hub input layer, and customers' convenience are all taken into account as the optimization objectives. Due to its promising performance in dealing with MO problems, the multiobjective particle swarm optimization method is employed to evaluate the optimization problem. The 2-point estimation method is used to model the existence uncertainties. The proposed framework is applied to the modified IEEE 34-node test system, and the obtained results demonstrate the efficiency and applicability of the proposed approach in real-world scenarios.

Game theoretical models of the cooperative carrier behavior

This paper presents a multi-level modeling approach which captures the cooperative behavior of carriers in maritime freight transportation networks. Ocean carriers, land carriers and port terminal operators are considered. Port terminal operators are regarded as a special type of carrier for modeling purposes. Ocean carriers are the leaders in a maritime shipping market. Port terminal operators are the followers of ocean carriers as well as the leaders of land carriers. For cooperating ocean and land carriers, compensation principle is used to find the optimal service charge and routing pattern that maximize their total profit, while port terminal operators act competitively. The concept of Stackelberg game is applied to a multi-level game, assuming a single ocean shipping company (leader) through an alliance. Subsequently, the paper considers cooperation between ocean carriers and port terminal operators, while individual carriers within the same group are considered to act competitively. Cooperative games within the same carrier group and between different groups of carriers are examined and compared with competitive games. A numerical example is presented to demonstrate the validity of the developed model.

Modeling Carrier Interactions in an International Freight Transport System

This paper presents a novel multi-level hierarchical approach which models carrier interactions in international maritime freight transportation networks. Ocean carriers, land carriers and port terminal operators are considered. Port terminal operators, providing transportation services within a port complex, are regarded as a special type of the carrier, based on their behavior. The carriers make pricing and routing decisions at different parts of the multimodal network, having hierarchical relationships. Ocean carriers are regarded as the leaders in a maritime shipping market. Port terminal operators are the followers of ocean carriers as well as the leaders of land carriers. The individual carrier problem is formulated at each level using Nash equilibrium to find the optimal service charge and routing pattern for which each carrier obtains the greatest profit. Interactions among different types of carriers are captured in a three-level model. The concept of multi-leader-follower game is applied to a multi-level game. A numerical example is used to demonstrate the validity of the developed three-level model.

Variational inequality model for cordon-based congestion pricing under side constrained stochastic user equilibrium conditions

A major objective of the practical implemented cordon-based congestion pricing schemes is to maintain the traffic conditions within the cordon area, which is rarely considered in most of the existing studies. Thus, this paper addresses the optimal toll charge pattern that can restrict the total inbound flow of each cordon to a predetermined threshold. The toll charges on all the entry links of one cordon are required to be identical, for the ease of implementation and users’ recognition. The users’ route choice behaviour is assumed to follow stochastic user equilibrium (SUE) with asymmetric link travel time functions. It is shown that such an optimal toll charge pattern can be attained by solving a SUE problem with side constraints. A variational inequality (VI) model is first proposed for the optimal toll pattern, where the monotone property of this model is rigorously proved. Then, a convergent self-adaptive prediction and correction method can be adopted for solving the VI model. It is shown that when used in practice, the solution method only needs traffic counts on entry links of each cordon.

Decentralized Charging Control of Large Populations of Plug-in Electric Vehicles

This paper develops a strategy to coordinate the charging of autonomous plug-in electric vehicles (PEVs) using concepts from non-cooperative games. The foundation of the paper is a model that assumes PEVs are cost-minimizing and weakly coupled via a common electricity price. At a Nash equilibrium, each PEV reacts optimally with respect to a commonly observed charging trajectory that is the average of all PEV strategies. This average is given by the solution of a fixed point problem in the limit of infinite population size. The ideal solution minimizes electricity generation costs by scheduling PEV demand to fill the overnight non-PEV demand “valley”. The paper's central theoretical result is a proof of the existence of a unique Nash equilibrium that almost satisfies that ideal. This result is accompanied by a decentralized computational algorithm and a proof that the algorithm converges to the Nash equilibrium in the infinite system limit. Several numerical examples are used to illustrate the performance of the solution strategy for finite populations. The examples demonstrate that convergence to the Nash equilibrium occurs very quickly over a broad range of parameters, and suggest this method could be useful in situations where frequent communication with PEVs is not possible. The method is useful in applications where fully centralized control is not possible, but where optimal or near-optimal charging patterns are essential to system operation.

Optimal patterning of heterogeneous surface charge for improved electrokinetic micromixing

Micromixing is a key step in realizing fast analysis time in many bio-chemical, biological and detection applications of lab-on-a-chip (LOC) devices. The conventional T-mixer design requires longer channel lengths and times to achieve complete mixing owing to its dependence on transverse diffusion. As the surface properties of the microchannel govern the electro-osmotic flow characteristics, surface heterogeneity (non-uniform zeta potentials) can be exploited to generate vortices or specific flow structures to improve the mixing performance. Previous studies have shown that localized circulations or non-axial flow induced due to the presence of heterogeneity augment micromixing performance. However, the effect of heterogeneous charge patterns on mixing performance has not been studied systematically. In this computational study, a binary numerical optimization problem is formulated to achieve best mixing performance by identifying the optimal heterogeneous charge pattern. The resulting optimal design generates the most favorable transverse flow structure to provide optimal mixing performance. Various other configurations (staggered, herringbone, etc.) are examined over a range of operating conditions. The optimal design is found to be superior for all operating conditions with over 3-fold improvement in mixing performance with respect to homogeneous T-mixer.

Search for an Optimal Five-Step Charging Pattern for Li-Ion Batteries Using Consecutive Orthogonal Arrays

Lithium-ion (Li-ion) batteries have emerged as the major power source for today's electronic products because they can offer advantages such as high energy density, low maintenance requirement, high open-circuit voltage, low self-discharge rate, and lack of memory effect. The performance and lifespan of Li-ion batteries are closely related to the quality of the charging pattern. Therefore, an optimal charging pattern is essential for Li-ion batteries to achieve shorter charging time and longer cycle life. In this paper, a Taguchi-based algorithm is presented. Consecutive orthogonal array techniques are utilized to determine the optimal charging pattern for the five-step constant current charging method. The problem formulation, implementation procedure, and parameter setting method are described and explained in detail. Experimental results show that the obtained charging pattern is capable of charging the Li-ion batteries to 95% capacity. Comparing to the conventional constant current-constant voltage method, the benefits of the obtained pattern are faster and safer charging and longer battery cycle life.