Showing papers on "State of charge published in 2012"

An Optimized EV Charging Model Considering TOU Price and SOC Curve

Abstract: Large-scale deployment of electric vehicles (EVs) is anticipated in the foreseeable future. Heavy intermittent charging load of EVs will create bottlenecks in supplying capacity and expose power system to severe security risks. In this paper, we propose an intelligent method to control EV charging loads in response to time-of-use (TOU) price in a regulated market. First, an optimized charging model is formulated to minimize the charging cost. Then, a heuristic method is implemented to minimize the charging cost considering the relation between the acceptable charging power of EV battery and the state of charge (SOC). Finally, the charging cost and energy demand in different time intervals are compared for both typical charging pattern and optimized charging pattern. Results show that the optimized charging pattern has great benefit in reducing cost and flatting the load curve if the peak and valley time periods are partitioned appropriately.

Smart electric vehicle (ev) charging and grid integration apparatus and methods

Abstract: An expert system manages a power grid wherein charging stations are connected to the power grid, with electric vehicles connected to the charging stations, whereby the expert system selectively backfills power from connected electric vehicles to the power grid through a grid tie inverter (if present) within the charging stations. In more traditional usage, the expert system allows for electric vehicle charging, coupled with user preferences as to charge time, charge cost, and charging station capabilities, without exceeding the power grid capacity at any point. A robust yet accurate state of charge (SOC) calculation method is also presented, whereby initially an open circuit voltage (OCV) based on sampled battery voltages and currents is calculated, and then the SOC is obtained based on a mapping between a previously measured reference OCV (ROCV) and SOC. The OCV-SOC calculation method accommodates likely any battery type with any current profile.

Autonomous Distributed V2G (Vehicle-to-Grid) Satisfying Scheduled Charging

Abstract: To integrate large scale renewable energy sources in the power grid, the battery energy storage performs an important role for smoothing their natural intermittency and ensuring grid-wide frequency stability. Electric vehicles have not only large introduction potential but also much available time for control because they are almost plugged in the home outlets as distributed battery energy storages. Therefore, vehicle-to-grid (V2G) is expected to be one of the key technologies in smart grid strategies. This paper proposes an autonomous distributed V2G control scheme. A grid-connected electric vehicle supplies a distributed spinning reserve according to the frequency deviation at the plug-in terminal, which is a signal of supply and demand imbalance in the power grid. As a style of EV utilization, it is assumed that vehicle use set next plug-out timing in advance. In such assumption, user convenience is satisfied by performing a scheduled charging for the plug-out, and plug-in idle time is available for the V2G control. Therefore a smart charging control is considered in the proposed scheme. Satisfaction of vehicle user convenience and effect to the load frequency control is evaluated through a simulation by using a typical two area interconnected power grid model and an automotive lithium-ion battery model.

High fidelity electrical model with thermal dependence for characterization and simulation of high power lithium battery cells

Abstract: The growing need for accurate simulation of advanced lithium cells for powertrain electrification demands fast and accurate modeling schemes. Additionally, battery models must account for thermal effects because of the paramount importance of temperature in kinetic and transport phenomena of electrochemical systems. This paper presents an effective method for developing a multi-temperature lithium cell simulation model with thermal dependence. An equivalent circuit model with one voltage source, one series resistor, and a single RC block was able to account for the discharge dynamics observed in the experiment. A parameter estimation numerical scheme using pulse current discharge tests on high power lithium (LiNi-CoMnO 2 cathode and graphite-based anode) cells under different operating conditions revealed dependences of the equivalent circuit elements on state of charge, average current, and temperature. The process is useful for creating a high fidelity model capable of predicting electrical current/voltage performance and estimating run-time state of charge. The model was validated for a lithium cell with an independent drive cycle showing voltage accuracy within 2%. The model was also used to simulate thermal buildup for a constant current discharge scenario.

Modeling the Benefits of Vehicle-to-Grid Technology to a Power System

Abstract: Electric vehicle (EV) numbers are expected to significantly increase in the coming years reflecting their potential to reduce air pollutants and greenhouse gas emissions. Charging such vehicles will impose additional demands on the electricity network but given the pattern of vehicle usage, the possibility exists to discharge the stored energy back to the grid when required, for example when lower than expected wind generation is available. Such vehicle-to-grid operation could see vehicle owners supplying the grid if they are rewarded for providing such services. This paper describes a model of an electric vehicle storage system integrated with a standardized power system (the IEEE 30-node power system model). A decision-making strategy is established for the deployment of the battery energy stored, taking account of the state of charge, time of day, electricity prices and vehicle charging requirements. Applying empirical data, the benefits to the network in terms of load balancing and the energy and cost savings available to the vehicle owner are analyzed. The results show that for the case under study, the EVs have only a minor impact on the network in terms of distribution system losses and voltage regulation but more importantly the vehicle owner's costs are roughly halved.

Real-Time Energy Management Algorithm for Mitigation of Pulse Loads in Hybrid Microgrids

Abstract: This paper presents a real-time energy management algorithm for hybrid ac/dc microgrids involving sustainable energy and hybrid energy storage. This hybrid storage system consists of super capacitors (SC) for ultra-fast load matching beside lithium-ion batteries for relatively long term load buffering. The energy management algorithm aims mainly at managing the energy within the system such that the effect of pulsed (short duration) loads on the power system stability is minimized. Moreover, an average annual saving of around 7% is achieved by shifting loads to off-peak hours. The expected energy needed during a future peak, the time of its occurrence and the current state of charge of both elements of the hybrid storage system are all examples of the inputs to the algorithm. A nonlinear regression technique is used to obtain mathematical models for the uncertain quantities including load and sustainable energy curves. The results show a significant improvement for the system in terms of voltage and power stability by applying the proposed algorithm.

Optimal Management Strategy of a Battery-Based Storage System to Improve Renewable Energy Integration in Distribution Networks

Abstract: The paper proposes the modeling and the optimal management of a hot-temperature (sodium nickel chloride) battery system coupled with wind generators connected to a medium voltage grid. A discrete-time model of the storage device reproducing the battery main dynamics (i.e., state of charge, temperature, current, protection, and limitation systems) has been developed. The model has been validated through some experimental tests. An optimal management strategy has been implemented based on a forward dynamic programming algorithm, specifically developed to exploit the energy price arbitrage along the optimization time horizon (“generation shifting”). Taking advantage of this strategy wind generation performances can be enhanced and adapted to load demand, obtaining an increased economic gain measured by the difference between the economic revenue obtained with and without the proposed generation shifting policy.

A hybrid battery model capable of capturing dynamic circuit characteristics and nonlinear capacity effects

Abstract: Summary form only given. A high-fidelity battery model capable of accurately predicting battery performance is required for proper design and operation of battery-powered systems. However, the existing battery models have at least one of the following drawbacks: 1) requiring intensive computation due to high complexity, 2) not applicable for electrical circuit design and simulation, and 3) not capable of accurately capturing the state of charge (SOC) and predicting runtime of the battery due to neglecting the nonlinear capacity effects. This paper proposes a novel hybrid battery model, which takes the advantages of an electrical circuit battery model to accurately predicting the dynamic circuit characteristics of the battery and an analytical battery model to capturing the nonlinear capacity effects for accurate SOC tracking and runtime prediction of the battery. The proposed battery model is validated by simulation and experimental studies for single-cell and multicell polymer lithium-ion batteries as well as for a lead-acid battery. The proposed model is applicable to other types and sizes of electrochemical battery cells. The proposed battery model is computational effective for simulation, design, and real-time management of battery-powered systems.

A Simple Sizing Algorithm for Stand-Alone PV/Wind/Battery Hybrid Microgrids

Abstract: In this paper, we develop a simple algorithm to determine the required number of generating units of wind-turbine generator and photovoltaic array, and the associated storage capacity for stand-alone hybrid microgrid. The algorithm is based on the observation that the state of charge of battery should be periodically invariant. The optimal sizing of hybrid microgrid is given in the sense that the life cycle cost of system is minimized while the given load power demand can be satisfied without load rejection. We also report a case study to show the efficacy of the developed algorithm.

Review of adaptive systems for lithium batteries State-of-Charge and State-of-Health estimation

Abstract: High energy battery systems have recently appeared as an alternative Internal-Conbustion-Engine (ICE) based vehicle's powertrains. As a conquence, over the last few years, automotive manufacturers focused their research on electrochemical storage for electric (EV) and hybrid electric vehicles (HEV). In a lot of hybrid or electric applications, Lithium based batteries are used. To protect Lithium batteries and optimize their utilisation, a good State-of-Charge determiation is necessary. So three adaptive system used in the literature are presented in this article, the Kalman Filter, the Artificial Neural Network and the Fuzzy Logic systems.

Demand profile study of battery electric vehicle under different charging options

Abstract: An increased research on electric vehicles (EV) and plug-in hybrid electric vehicles (PHEV) deals with their flexible use in electric power grids. Several research projects on smart grids and electric mobility are now looking into realistic models representing the behavior of an EV during charging, including nonlinearities. In this work, modeling, simulation and testing of the demand profile of a battery-EV are conducted. Realistic work conditions for a lithium-ion EV battery and battery charger are considered as the base for the modeling. Simulation results show that EV charging generates different demand profiles into the grid, depending on the applied charging option. Moreover, a linear region for the control of EV chargers is identified in the range of 20-90% state-of-charge (SOC). Experiments validate the proposed model.

Determination of Short-Term Power Dispatch Schedule for a Wind Farm Incorporated With Dual-Battery Energy Storage Scheme

Abstract: A battery energy storage scheme to enable short-term dispatch commitment from a grid-connected wind-turbine generating power station is considered. Among the various types of energy storage medium, technical factors leading to the selection of battery are explained. The scheme utilizes two battery energy storage systems (BESS) in which the generated wind power charges one BESS while concurrently, the second BESS is to discharge power into the grid. The role of the two BESS interchanges when the BESS reaches specified state of charge/discharge. Furthermore, based on forecasted charging wind power and the monitored states of charge of the two BESS, the discharge power level from the generating station is determined and scheduled a few hours ahead. The dispatch scheme maximizes wind energy harnessed, achieved with the minimum number of the BESS switch-overs. The design thus prolongs the service life of the BESS. Numerical examples to demonstrate the performance of the scheme are also included.

A Method for Online Capacity Estimation of Lithium Ion Battery Cells Using the State of Charge and the Transferred Charge

Abstract: In this paper, a method to estimate the capacity of individual lithium ion battery cells during operation is presented. When having two different states of charge of a battery cell as well as the transferred charge between these two states, the capacity of the battery cell can be estimated. The method is described in detail and validated on a battery cell with a current pulse test cycle. It is then applied to a real-life cycle; the accuracy is analyzed and discussed.

Online Estimation of Peak Power Capability of Li-Ion Batteries in Electric Vehicles by a Hardware-in-Loop Approach

Abstract: Battery peak power capability estimations play an important theoretical role for the proper use of the battery in electric vehicles. To address the failures in relaxation effects and real-time ability performance, neglecting the battery’s design limits and other issues of the traditional peak power capability calculation methods, a new approach based on the dynamic electrochemical-polarization (EP) battery model, taking into consideration constraints of current, voltage, state of charge (SoC) and power is proposed. A hardware-in-the-loop (HIL) system is built for validating the online model-based peak power capability estimation approach of batteries used in hybrid electric vehicles (HEVs) and a HIL test based on the Federal Urban Driving Schedules (FUDS) is used to verify and evaluate its real-time computation performance, reliability and robustness. The results show the proposed approach gives a more accurate estimate compared with the hybrid pulse power characterization (HPPC) method, avoiding over-charging or over-discharging and providing a powerful guarantee for the optimization of HEVs power systems. Furthermore, the HIL test provides valuable data and critical guidance to evaluate the accuracy of the developed battery algorithms.

State-of-Charge Monitoring and Electrolyte Rebalancing Methods for the Vanadium Redox Flow Battery

Abstract: A major issue with all flow batteries is the control of the imbalance between the two half-cell electrolytes that arises as a result of the differential transfer of ions across the membrane and the inevitable gassing side reactions that can occur during charging. While a number of methods are available to rebalance electrolyte state of charge and restore capacity, reliable methods are needed to monitor the state-of-charge of each individual half-cell solution in order to determine the appropriate action to be taken by the battery control system. In this study different methods of state-of-charge monitoring have been considered for application in the All-Vanadium Redox Flow Battery (VRB). Half-cell potentials and electrolyte conductivities were calibrated as a function of state-of-charge and evaluated for state-of-charge monitoring of individual half-cell electrolytes for the purpose of capacity restoration and control. An empirical model based on experimental conductivity data has been shown to provide accurate predictions, with an average error of 0.77%, of the conductivity of the positive half-cell electrolyte as a potential state-of-charge detection tool. Separate monitoring of the two half-cell electrolyte potentials has also been used to determine the state-of-charge of each half-cell solution in order to detect system imbalance. This was used in small laboratory cell tests to determine necessary actions to restore capacity by either remixing the two solutions, or by using chemical rebalancing methods, depending on the cause of the solution imbalance.

Online Estimation of State of Charge in Li-Ion Batteries Using Impulse Response Concept

Abstract: Lithium-ion batteries exhibit high levels of energy and power density among electrochemical batteries. These attributes make them suitable as the energy storage system in electric, hybrid electric vehicle, and plug-in vehicles (EV/HEV/PHEV). One of the important requirements in automotive batteries is to monitor their real time state-of-charge (SOC) and state-of-health (SOH). Open circuit voltage, as one parameter used for predicting the SOC in the battery, is not readily available during charge and discharge cycles. In this paper a new method for prediction of the terminal voltage in li-ion batteries based on the impulse response concept has been proposed. By obtaining the impulse response of the li-ion battery, one can use the terminal current to predict the output voltage of the battery. Online comparison of the predicted and measured terminal voltage provides a tool for online monitoring of the SOH and SOC.