This paper presents the use of an energy recycling technique to extract the intrinsic parameters of lead–acid batteries. The charging and discharging currents of the battery under test are programmed by controlling a bidirectional dc–dc converter to profile the power flow between the battery and a supercapacitor. The sampled battery voltage and current information over the charging and discharging periods are used to estimate the parameters of a high-order electrical battery model with a modified particle swarm optimization algorithm and compare with the battery voltage and current predicted with the extracted parameters.  With the energy recycling mechanism, the proposed parameter extraction process is environment friendly and has low power dissipation, thus increasing the power handling density and allowing long testing duration. A prototype that can extract the intrinsic parameters of eight different types of 12 V, 130 A lead–acid batteries has been built. Its performance has been evaluated with different charging and discharging profiles. The estimated parameters are favorably verified with the theoretical predictions, results obtained by the extended Kalman filter method, and results obtained on a calibrated commercial battery testing system. Results reveal that testing batteries with both charging and discharging processes gives a more accurate prediction of battery performance.

Extraction of Intrinsic Parameters of Lead–Acid Batteries Using Energy Recycling Technique

Due to the global energy crisis and air pollution, the demand for electric vehicles (EVs) and battery storage systems grows at a gallop. To support this growth, it is important to have an effective exploitation of electrochemical based energy storage system with a reliable battery management system (BMS). The remaining useful life (RUL) prediction and estimation of different age batteries are necessary for BMS design. Terminal voltage, current and surface temperature are three main types of data that have significant impacts on predicting the battery's RUL. In this paper, a mathematical model based on regression analysis is formulated to estimate the batterys RUL. Additionally, the corresponding relationship between discharge curve and battery's age is analyzed base on the battery's capacity variety with using time. Finally, the proposed model is validated with experiments on valve-regulated lead acid (VRLA) batteries.

Modeling discharge characteristics for predicting battery remaining life

The invention provides a method of building a battery DC inner resistance function. The method comprises the following steps: corresponding battery DC inner resistance data of a battery under different battery SOCs (State of Charge), multiple different charging/discharging currents and multiple different ambient temperatures are acquired; according to the acquired battery DC inner resistance data, a function of the battery DC inner resistance relative to the battery SOCs, the charging/discharging currents and the ambient temperatures is built; a heat production model, a heat transfer model and a heat dissipation model for the battery are built, and according to the heat production model, the heat transfer model and the heat dissipation model, the surface temperature of the battery is predicted in real time; and according to the function of the battery DC inner resistance relative to the battery SOCs, the currents and the ambient temperatures and the surface temperature of the battery, a function of the battery DC inner resistance relative to the battery SOCs, the charging/discharging currents and the surface temperature of the battery is built. The function relationship between the battery SOCs, the current and the surface temperature of the battery and the battery DC inner resistance can be described simply, comprehensively, accurately and in real time, realization is easy, and engineering applications are facilitated.

Method of building battery DC inner resistance function

Nowadays energy storage systems, such as batteries, are essential for electric vehicles and renewable energy sources. One of the important aspects is to model both the electrical and thermic battery behaviors. Another important aspect is to find a modeling procedure whereby the parameters of these models are found. In literature, different models and modeling procedures are present. This paper presents a simplified identification procedure applied to an electric model for lithium-ion batteries. This model takes into account the electrical behavior of the battery as a function of different factors, such as the state of discharge, discharge current and temperature. Experimental tests were carried out in order to characterize and test the electric model. Finally, some simulation tests were made in Matlab/Simulink to compare experimental and simulated results.

Lithium-ion battery: A simplified modeling procedure and system simulation

A DC microgrid comprised of a random power source, a random impedance load, a fixed ballast and a stabilizer unit (lead acid battery + ultra-capacitor bank) was modeled and constructed. A fuzzy-logic control algorithm was implemented to demonstrate stabilization of a DC microgrid to a given tolerance while demonstrating improved management of the storage systems when compared against a tradition proportional-integral control algorithm.

/pdf/dc-microgrid-stabilization-through-fuzzy-control-of-4mmy9yuql3.pdf

DC Microgrid Stabilization Through Fuzzy Control of Interleaved Heterogeneous Storage Elements

Modeling the external characteristics of the battery precisely is a basic issue for effective battery management in energy storage systems. It is difficult because many inherent factors influence the external characteristics, but only few information, such as terminal voltage, current and surface temperature, can be obtained for modeling. This paper proposes a simple method for modeling the discharge characteristics of the battery. The basic patterns of discharge curves and their relationship with discharge current are analyzed. A mathematic model is built based on the method .The model is verified with experiments on valve-regulated lead-acid (VRLA) batteries.

A Battery Modeling Method and Its Verification in Discharge Curves of Lead-Acid Batteries

The invention relates to a method for measuring dynamic external characteristics of a power battery, and belongs to the technical field of a battery. The method is characterized in that the dynamic external characteristics of the power battery near different working currents can be obtained through a method of stacking dynamic excitation on the different working currents, time-varying characteristics which are mixedly stacked in the dynamic external characteristics of the power battery can be approximately removed based on a constant-current characteristic curve of the power battery and a curve differencing method, and the accurate measuring on the dynamic external characteristics of the power battery can be finally realized. According to the method disclosed by the invention, different dynamic characteristic information in the power battery under different working current conditions can be more fully revealed, and thus high modeling accuracy can be obtained; the method not only can be offline used by a power battery manufacturer to test basic parameters of the power battery, but also can be used for online testing the power battery.

Geng Hua

Papers

A Battery Modeling Method and Its Verification in Discharge Curves of Lead-Acid Batteries

Method for measuring dynamic external characteristics of power battery