Showing papers on "State of charge published in 2009"

State-of-Charge (SOC)-Balancing Control of a Battery Energy Storage System Based on a Cascade PWM Converter

Abstract: Renewable energy sources such as wind turbine generators and photovoltaics produce fluctuating electric power. The fluctuating power can be compensated by installing an energy storage system in the vicinity of these sources. This paper describes a 6.6-kV battery energy storage system based on a cascade pulsewidth-modulation (PWM) converter with focus on a control method for state-of-charge (SOC) balancing of the battery units. A 200-V, 10-kW, 3.6-kWh (13-MJ) laboratory system combining a cascade PWM converter with nine nickel metal hydride (NiMH) battery units is designed, constructed, and tested to verify the validity and effectiveness of the proposed balancing control.

Control Strategies for Battery Energy Storage for Wind Farm Dispatching

Abstract: Integrating a battery energy storage system (BESS) with a large wind farm can smooth out the intermittent power from the wind farm. This paper focuses on development of a control strategy for optimal use of the BESS for this purpose. The paper considers a conventional feedback-based control scheme with revisions to incorporate the operating constraints of the BESS, such as state of charge limits, charge/discharge rate, and lifetime. The goal of the control is to have the BESS provide as much smoothing as possible so that the wind farm can be dispatched on an hourly basis based on the forecasted wind conditions. The effectiveness of this control strategy has been tested by using an actual wind farm data. Finally, it is shown that the control strategy is very important in determining the proper BESS size needed for this application.

Optimizing a Battery Energy Storage System for Frequency Control Application in an Isolated Power System

Abstract: This paper presents a method for optimal sizing and operation of a battery energy storage system (BESS) used for spinning reserve in a small isolated power system. Numerical simulations are performed on a load-frequency control (LFC) dynamic simulator of the isolated network. A novel control algorithm using adjustable state of charge limits is implemented and tested on a BESS dynamic model. An optimal sizing procedure of the BESS is developed for an isolated power system in order to achieve highest expected profitability of the device. The BESS can increase significantly the power system stability, the grid security, and the planning flexibility for a small isolated power system with low grid inertia. Meanwhile, it fulfills the frequency control requirements with a high expected economic profitability.

Lithium-ion batteries life estimation for plug-in hybrid electric vehicles

Abstract: This paper deals with life estimation of lithium batteries for plug-in hybrid electric vehicles (PHEVs). An aging model, based on the concept of accumulated charge throughput, has been developed to estimate battery life under “real world” driving cycles (custom driving cycles based on driving statistics). The objective is to determine the “damage” on the life related to each driving pattern to determine equivalent miles/years. Results indicates that Lithium-ion batteries appear to be 10 year/150,000 mile capable, provided that they are not overcharged, nor consistently operated at high temperatures, nor in charge sustaining mode at a very low state of charge.

New Battery Model and State-of-Health Determination Through Subspace Parameter Estimation and State-Observer Techniques

Abstract: This paper describes a novel adaptive battery model based on a remapped variant of the well-known Randles' lead-acid model. Remapping of the model is shown to allow improved modeling capabilities and accurate estimates of dynamic circuit parameters when used with subspace parameter-estimation techniques. The performance of the proposed methodology is demonstrated by application to batteries for an all-electric personal rapid transit vehicle from the urban light transport (ULTRA) program, which is designated for use at Heathrow Airport, U.K. The advantages of the proposed model over the Randles' circuit are demonstrated by comparisons with alternative observer/estimator techniques, such as the basic Utkin observer and the Kalman estimator. These techniques correctly identify and converge on voltages associated with the battery state-of-charge (SoC), despite erroneous initial conditions, thereby overcoming problems attributed to SoC drift (incurred by Coulomb-counting methods due to overcharging or ambient temperature fluctuations). Observation of these voltages, as well as online monitoring of the degradation of the estimated dynamic model parameters, allows battery aging (state-of-health) to also be assessed and, thereby, cell failure to be predicted. Due to the adaptive nature of the proposed algorithms, the techniques are suitable for applications over a wide range of operating environments, including large ambient temperature variations. Moreover, alternative battery topologies may also be accommodated by the automatic adjustment of the underlying state-space models used in both the parameter-estimation and observer/estimator stages.

Impedance Observer for a Li-Ion Battery Using Kalman Filter

Abstract: Most methods for state-of-charge or state-of-health prognostics are impedance based. Impedance models must be as simple as possible to be implemented on embedded applications but as accurate as possible to represent the main electrochemical phenomena. The parameters of such models can be identified using impedance spectroscopy. However, the electrochemical features change in relation to numerous parameters, such as temperature or aging, which involves updating the model of the battery online. This paper deals with the use of an extended Kalman filter (EKF) for the observation of the parameters of a Li-ion battery lumped model. First, this paper will focus on the electrical model that can be used to represent the main electrochemical phenomena in the battery. Then, mathematical considerations about the EKF are reminded to be applied to the observation of the impedance parameters of the battery. This method has been validated on an urban driving cycle of a hybrid electric vehicle.

Predictive Reference Signal Generator for Hybrid Electric Vehicles

Abstract: A novel model-based and predictive energy supervisory controller for hybrid electric vehicles (HEVs) is presented. Its objective is to minimize the fuel consumption (FC) of HEVs using only the information on the current state of charge (SoC) of the battery and data available from a standard onboard navigation system. This objective is achieved using a predictive reference signal generator (pRSG) in combination with a nonpredictive reference tracking controller for the battery SoC. The pRSG computes the desired battery SoC trajectory as a function of vehicle position such that the recuperated energy is maximized despite the constraints on the battery SoC. To compute the SoC reference trajectory, only the topographic profile of the future road segments and the corresponding average traveling speeds must be known. Simulation results of the proposed predictive strategy show substantial improvements in fuel economy in hilly driving profiles, compared with nonpredictive strategies. A parallel HEV is analyzed in this paper. However, the proposed method is independent of the powertrain topology. Therefore, the method is applicable to all types of HEVs.

A new SOH prediction concept for the power lithium-ion battery used on HEVs

Abstract: One of the most important tasks of the battery management system (BMS) is to estimate the battery states which mainly include the State of Charge (SOC) and State of Health (SOH). Compared with the SOC estimation technology, which progresses a lot currently, the study of SOH prediction method is in its junior state. In this paper, a SOH prediction concept was proposed. Main points of this concept include the aging process of the battery, the definition of the SOH, and prediction of the battery's healthy state etc. Aiming at the application mode of the battery packs on hybrid electric vehicles (HEVs), ageing processes of the battery were discussed and several accelerated life test results were listed. Then according to the aging process studies, a power- reflecting SOH definition was proposed. Based on these, a parameter system identification based SOH prediction method was designed. To validate the SOH prediction concept we presented, a simulation test was designed, and test result show that the concept is feasible to predict SOH online.

Redox flow battery system for distributed energy storage

Abstract: A large stack redox flow battery system provides a solution to the energy storage challenge of many types of renewable energy systems. Independent reaction cells arranged in a cascade configuration are configured according to state of charge conditions expected in each cell. The large stack redox flow battery system can support multi-megawatt implementations suitable for use with power grid applications. Thermal integration with energy generating systems, such as fuel cell, wind and solar systems, further maximize total energy efficiency. The redox flow battery system can also be scaled down to smaller applications, such as a gravity feed system suitable for small and remote site applications.

System and method for dual energy storage management

Abstract: A dual-energy storage system is described, having two energy sources: (a) a fast- energy storage devices (FES) such as an ultracapacitor, and (b) a long duration or steady power device, such as a fuel-cell or battery. A power converter or controller executes an energy management algorithm to determine when to provide bursts of additional power/current from the fast-energy storage device, and when to recharge the fast-energy storage device. A method is further described of adaptively managing the state of charge of an ultracapacitor or other Fast Energy Storage device in the dual energy storage system of a Plug-in Hybrid propulsion system. The method provides good protection of the battery, good performance, and minimizes the required capacity of the ultracapacitor.

Frequency responsive charge sustaining control of electricity storage systems for ancillary services on an electrical power grid

Abstract: Systems, apparatus, and methods are provided for maintaining the state of charge of energy storage devices such as batteries, flywheel, capacitors, or other technologies that are energetically coupled with the electricity grid to support ancillary services. To reliably respond to requests to regulate the grid, the charge on the energy storage device is sustained or restored to a specified range in a manner that optimizes the readiness of the energy storage device to supply ancillary services in light of the condition of the grid. A state of charge (SOC) of the energy storage device and the grid frequency may be monitored. When a request from the operator to regulate the grid frequency is not being serviced, the charge of the energy storage device may be increased or decreased so that the charge may be sustained within the specific range. Once the SOC falls outside of the first range, charge may be added to or removed from the energy storage device when the grid frequency has appropriate values, e.g. if the grid frequency is respectively above a first setpoint or below a second setpoint.

Intelligent energy management system simulator for PHEVs at municipal parking deck in a smart grid environment

Abstract: There is a need for in-depth study of technologies that will affect the utility industry in a time horizon of less than 20 years. One such technology is the plug-in vehicle (PHEV); there is a need for energy management when a large number of plug-in hybrid vehicles penetrate the market. In this paper, we propose an “intelligent energy management system (iEMS)” that intelligently allocates power to the vehicle battery chargers through real time monitoring and control, to ensure optimal usage of available power, charging time and grid stability. We begin by conceptualization of the system architecture and description of its operation and provide a theoretical framework for system modeling. A detailed PHEV battery model and state of charge estimation algorithm are also being developed to simulate different PHEVs to be recharged at a municipal parking deck. We will present the simulator we have developed for representing the iEMS using Matlab/Simulink and discuss obtained results and future directions.

Power supply system and vehicle with the system

Abstract: A vehicle includes a charging unit receiving electric power from an external power source and externally charging a power storage unit. When a connector unit is coupled to the vehicle and a state ready for charging by the external power source is attained, a controller predicts degradation ratio of the power storage unit at the time point of completion of external charging based on degradation characteristic of the power storage unit in connection with SOC and battery temperature obtained in advance, and sets target state of charge of each power storage unit based on the battery temperatures so that the predicted degradation ratio does not exceed tolerable degradation ratio at the time point of completion of external charging. Then, the controller controls corresponding converters such that SOCs of power storage units attain the target states of charge.

An enhanced coulomb counting method for estimating state-of-charge and state-of-health of lead-acid batteries

Abstract: This paper proposes an enhanced coulomb counting method based on the depth-of-discharge (DOD) to estimate the state-of-charge (SOC) and state-of-health (SOH) for valve regulated lead-acid (VRLA) batteries. The losses at different discharging currents are accounted for compensation to the releasable capacities. Furthermore, the SOH is revaluated at the depletion and fully charged states by the maximum releasable capacity and the charged capacity, consequently leading to more accurate SOC estimation. Through the experiments that emulate practical operations, the experimental results reveal that the maximum error is less than 6 %.

Battery pack modeling for the analysis of battery management system of a hybrid electric vehicle

Abstract: Battery forms a critical part of the hybrid electric vehicle (HEV) drivetrain. An important constraint to the effective performance and reliability of the battery is its unpredictable internal resistance variation along the driving cycle. Temperature has a considerable effect on this internal resistance and thus the battery management system monitors cell and battery pack temperature in accordance with the state-of-charge to prevent thermal runaway. Li-ion batteries which offer possible solutions to the HEVs energy and power density demands thus need to have a good thermal management system in order to enhance their performance. This paper aims to develop a battery pack model that would analyze the variation of internal resistance as a function of temperature. The study of the losses would help in designing a cost effective efficient battery management system.

Characterizing naturalistic driving patterns for Plug-in Hybrid Electric Vehicle analysis

Abstract: While much of the previous research relies on Federal Driving Schedules originally developed for emission certification tests of conventional vehicles, consumer acceptance and market penetration will depend on PHEV performance under realistic driving conditions. Therefore, characterizing the actual driving is essential for PHEV design and control studies, and for establishing realistic forecasts pertaining to vehicle energy consumption and charging requirements. To achieve this goal, we analyze naturalistic driving data generated in Field Operational Tests (FOT) of passenger vehicles in Southeast Michigan. The FOT were originally conceived for evaluating driver interaction with advanced safety systems, but the databases are rich with information pertaining to vehicle energy. After the initial statistical analysis of the vehicle speed histories, the naturalistic driving schedules are used as input to the PHEV computer simulation to predict energy usage as a function of trip length. The highest specific energy, i.e. energy per mile, is critical for battery and motor sizing. As an illustration of the impact of actual driving, the low-energy and high-energy driving patterns would require PHEV20 battery sizes of 6.12 kWh and 13.6 kWh, respectively. This is determined assuming that the minimum state of charge (SOC) is 40%. In addition, the naturalistic driving databases are mined for information about vehicle resting time, i.e. time spent at typical locations during the 24-hour period. The locations include “home”, “work”, “large-business” such as a large retail store, and “small business”, such as a gas station, and finally “residential” other than home. The characterization of vehicle daily missions supports analysis of charging schedules, as it indicates times spent at given locations as well as the likely battery SOC at the time of arrival.

Power system for a hybrid fuel cell vehicle that employs a floating base load strategy

Abstract: A fuel cell system employing a floating base load hybrid strategy for reducing fast voltage transients of a FCPM. A power request signal is applied to an average power calculation processor that calculates the average power requested over a predetermined previous period of time. A weighting function processor provides a weighting function based on the state of charge of an EESS. The power available from the FCPM and the EESS is applied to a power comparison processor. The available power is compared to the power request to provide a difference value between what is currently being provided and what is desired. The difference value is compared to power limit values of the EESS. The output value of this comparison is added to a filtered value to generate a signal for the change in the output power of the fuel cell stack based on the power request.

Method and apparatus for determining state of charge of a battery

Abstract: A method and apparatus for determining the state of charge (SOC) of a battery is discussed. The method involves measuring the terminal voltage across the battery and the current flowing through the battery at a plurality of different times and fitting a line equation with a slope and an intercept to the terminal voltage and current data. The open-circuit voltage (OCV) is calculated from the intercept of the linear equation and the SOC is determined from the OCV by reference to a lookup table.

Vehicle and method for controlling vehicle

Abstract: A vehicle is equipped with a battery configured so as to be rechargeable, a motor generator configured so as to generate the driving force of the vehicle by use of electric power stored in the battery, a switch configured so as to switch between generation of a command for extending the use period of the battery and stop of generation of the command, and an ECU for controlling the state of charge of the battery. The ECU sets the control range of SOC of the battery. When the switch stops generation of the command, the ECU sets the control range to a first range. Meanwhile, when a command is generated by the switch, the ECU sets the control range to a second range narrower than the first range.

Battery capacity estimating method and apparatus

Abstract: A method for accurately estimating battery capacity based on a weighting function is provided. The disclosed system monitors battery current and uses the monitored battery current to calculate the state of charge (SOCbyAh) of the battery. The system also measures the open circuit voltage (OCV) of the battery when the system is at rest, rest being determined by achieving a current of less than a preset current value for a period of time greater than a preset time period. The state of charge of the battery is calculated from the OCV (SOCbyOCV). The weighting function is based on ΔSOCbyAh and ΔSOCbyOCV, where ΔSOCbyAh is equal to SOCbyAh First time minus SOCbyAh Second time , and where ΔSOCbyOCV is equal to SOCbyOCV First time minus SOCbyOCV Second time . The weighting function also takes into account the errors associated with determining SOCbyAh and SOCbyOCV.

The method for measuring soc of a battery in battery management system and the apparatus thereof

Abstract: This invention is related to a method and an apparatus for choosing SOCi (State Of Charge based on current) or SOCv (State of Charge based on voltage) as the SOC (State Of Charge) of a battery depending on a condition in a battery management system by using an equivalent circuit model In this invention, a method for measuring SOC of a battery in a battery management system is characterized by comprising the steps of: obtaining voltage data and temperature data by measuring the current, voltage and temperature of a battery; calculating SOCi by accumulating the current data; calculating open circuit voltage by using an equivalent circuit model which simply presents the current data, the voltage data and the battery through an electric circuit; calculating SOCv by using the temperature data and the open circuit voltage; and choosing at least one of the SOCi and the SOCv as SOC of the battery by using the SOCi and the SOCv based on the judgment on the current state of a vehicle for a certain time interval

Power management systems and methods in a hybrid vehicle

Abstract: A system and method of determining and applying power split ratios to power sources within hybrid vehicles. The power split ratio is determined using a two-scale dynamic programming technique to achieve optimal state of charge depletion over the course of a trip. On the macro-scale level, a global state of charge profile is created for the entire trip. On the micro-scale level, the state of charge profile and accompanying power split ratio is recalculated at the end of each segment as the vehicle proceeds along the trip. Various trip modeling techniques are used to provide constraints for the dynamic programming.

Supervisory system controller for use with a renewable energy powered radio telecommunications site

Abstract: A supervisory system controller for controlling and monitoring the generation of electrical energy from renewable sources and management methods for the storage of energy so generated and interconnecting the energy-generating elements, storage and load. The supervisory system controller operates to maximum the power transfer from a wind turbine to a battery by automatically varying the threshold levels at which turbine dump loads are switched based on system inputs and measurements. The method conserves generator fuel by delaying a scheduled generator maintenance running period such that it occurs when renewable energy availability is predicted to be low and battery is in a reduced state of charge. Further modifications and management methods are also provided.