• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1996년도 추계학술대회 논문집 학회본부
• /
• pp.355-358
• /
• 1996

Electrical Power System (EPS) of Electric Vehicle which consists of batteries, motor and driving subsystem, has been modeled. A battery model is modeled with an electrical circuit representing a characteristics of real battery. Driving subsystem is modeled as three different level namely exact, average and functional models. Load profile includes road information, speed profile and EV mechanical parameters, which are incorporated into a reference torque in the driving subsystem model. A system model is integrated to simulate the performance of electric vehicle such as energy balance, battery status, and electrical stress of each subsystem.

• 전력전자학회논문지
• /
• 제27권4호
• /
• pp.316-324
• /
• 2022

This paper uses seasonal auto-regressive integrated moving average (S-ARIMA), which is efficient in seasonality between time-series models, to predict the degradation tendency for lithium-ion batteries and study a method for improving the predictive performance. The proposed method analyzes the degradation tendency and extracted factors through an electrical characteristic experiment of lithium-ion batteries, and verifies whether time-series data are suitable for the S-ARIMA model through several statistical analysis techniques. Finally, prediction of battery aging is performed through S-ARIMA, and performance of the model is verified through error comparison of predictions through mean absolute error.

• 소성∙가공
• /
• 제32권3호
• /
• pp.136-144
• /
• 2023

This study analyzed the mechanical behavior of lithium-ion battery pouch material and predicted its formability. A homogenization method was used to evaluate the physical properties of the pouch, and a new hardening model was developed. The yield function for the plastic model was optimized, and the anisotropic property was determined. Also, the forming limits were measured and predicted using the M-K forming limit diagram. Finally, a square cup drawing experiment confirmed the accuracy of the measured mechanical properties and the formability calculation.

• 전기학회논문지
• /
• 제63권8호
• /
• pp.1085-1091
• /
• 2014

A model based SOC estimation scheme using parameter identification is described and applied to a Lithium-ion battery module that can be installed in electric vehicles. Simulation studies are performed to verify the effect of sensor faults on the SOC estimation results for terminal voltage sensor and load current sensor. The sensor faults should be detected and isolated as soon as possible because the SOC estimation error due to any sensor fault seriously affects the overall performance of the BMS. A new fault detection and isolation(FDI) scheme by which the fault of terminal voltage sensor and load current sensor can be detected and isolated is proposed to improve the reliability of the BMS. The proposed FDI scheme utilizes the parameter estimation of an input-output model and two fuzzy predictors for residual generation; one for terminal voltage and the other for load current. Recently developed dual polarization(DP) model is taken to develope and evaluate the performance of the proposed FDI scheme. Simulation results show the practical feasibility of the proposed FDI scheme.

• 전력전자학회논문지
• /
• 제5권5호
• /
• pp.435-442
• /
• 2000

리튬폴리머전지의 전기적인 특성을 평가하고 이것을 시스템 측면에서 고찰할 수 있는 이론적인 토대를 마련하기 위하여 본 논문에서는 전지의 전기적인 특성평가를 위한 전기적모델링 기법에 관하여 고찰하였다. 실제 제작된 리튬폴리머전지의 특성자료를 바탕으로 R-L-C 모델을 이용한 동적해석방식과 PSpice 모델을 이용한 정적해석방식을 통하여 리튬폴리머전지의 전기적 특성을 해석하였다. 각 모델의 풍/방전시의 전기적 특성을 고찰하고 충/방전조건에 따른 전지의 단자전압등 특성변수의 변화를 실제 제작된 리튬폴리머전지와 비친, 검토하여 그 타당성을 검증하였다.

• Journal of Power Electronics
• /
• 제12권5호
• /
• pp.778-786
• /
• 2012

In this paper, a novel scheme for the condition monitoring of lithium polymer batteries is proposed, based on the sigma-point Kalman filter (SPKF) theory. For this, a runtime-based battery model is derived, from which the state-of-charge (SOC) and the capacity of the battery are accurately predicted. By considering the variation of the serial ohmic resistance ($R_o$) in this model, the estimation performance is improved. Furthermore, with the SPKF, the effects of the sensing noise and disturbance can be compensated and the estimation error due to linearization of the nonlinear battery model is decreased. The effectiveness of the proposed method is verified by Matlab/Simulink simulation and experimental results. The results have shown that in the range of a SOC that is higher than 40%, the estimation error is about 1.2% in the simulation and 1.5% in the experiment. In addition, the convergence time in the SPKF algorithm can be as fast as 300 s.

• Journal of Power Electronics
• /
• 제15권4호
• /
• pp.1006-1017
• /
• 2015

This paper presents a finite control set model predictive control (FCS-MPC) strategy for the AC/DC matrix converter used in grid-connected battery energy storage system (BESS). First, to control the grid current properly, the DC current is also included in the cost function because of input and output direct coupling. The DC current reference is generated based on the dynamic relationship of the two currents, so the grid current gains improved transient state performance. Furthermore, the steady state error is reduced by adding a closed-loop. Second, a Luenberger observer is adopted to detect the AC input voltage instead of sensors, so the cost is reduced and the reliability can be enhanced. Third, a switching state pre-selection method that only needs to evaluate half of the active switching states is presented, with the advantages of shorter calculation time, no high dv/dt at the DC terminal, and less switching loss. The robustness under grid voltage distortion and parameter sensibility are discussed as well. Simulation and experimental results confirm the good performance of the proposed scheme for battery charging and discharging control.

• 드라이브 ㆍ 컨트롤
• /
• 제16권1호
• /
• pp.45-53
• /
• 2019

The objective of this study was to design and model the PEM fuel cell excavator with supercapacitor/battery hybrid power source to increase efficiency as well as eliminate greenhouse gas emission. With this configuration, the system can get rid of the internal combustion engine, which has a low efficiency and high emission. For the analysis and simulation, the governing equations of the PEM system, the supercapacitor and battery were derived. These simulations were performed in MATLAB/Simulink environment. The hydraulic modeling of the excavator was also presented, and its model implemented in AMESim and studied. The whole system model was built in a co-simulation environment, which is a combination of MATLAB/Simulink and AMESim software. The simulation results were presented to show the performance of the system.

• 전력전자학회논문지
• /
• 제26권6호
• /
• pp.381-389
• /
• 2021

Most diagnosis approaches rely on historical failure data that might not be feasible in real operating conditions because the battery voltage and internal parameters are nonlinear according to various operating conditions, such as cell-to-cell configuration and initial condition. To overcome this issue, the estimator and the predictor require integrated approaches that consider comprehensive data, with the degradation process and measured data taken into account. In this paper, vector autoregressive models (VAR) with various parameters that affect overdischarge to the cell in the battery pack were constructed, and the cell-to-cell parameters were identified using an adaptive model to analyze the influence of failure prognosis. The theoretical analysis is validated using experimental results in terms of the feasibility and advantages of fault prognosis.

• Korean Chemical Engineering Research
• /
• 제60권3호
• /
• pp.363-370
• /
• 2022

본 논문에서는 전기자동차용 배터리 충/방전 상태 추정의 정확도를 개선하기 위해 칼만 필터(Kalman Filter, KF) 알고리즘과 등가회로모델(Equivalent Circuit Model)을 활용한 State Of Charge (SOC) 추정 방법을 적용하였다. 특히 노화된 배터리 용량을 함께 추정 가능한 관측기(observer)를 설계하였다. 우선 노화가 없는 경우, 칼만 필터를 이용하여 SOC를 단일 추정하면, 관측기 없이 모델로 계산된 경우와 비교하여 평균 절대 오차율이 1.43%(관측기 미사용)에서 0.27%(관측기 사용)로 감소하였다. 차량 주행상태에서는 전류가 고정되지 않아 SOC와 배터리 용량을 모두 추정하는 것에 일반적인 KF 혹은 Extended KF 알고리즘을 이용할 수 없다. 배터리 노화에 의한 용량 변화는 단시간에 일어나지는 않다는 점에 착안하여, 충전 시 배터리 용량 추정을 주기적으로 실시하는 전략을 제시하였다. 충전 모드에서는 일정 구간마다 전류가 고정되기에, 해당 상황에서 배터리 노화 용량을 SOC와 함께 추정 전략을 제시하였다. 전류가 고정된 상태에서 SOC 추정의 평균 절대 오차율은 0.54% 였으며, 용량 추정의 평균 절대 오차율은 2.24%로 나타났다. 충전상태에서 전류가 고정됨으로 일반적인 EKF를 활용하여 배터리 용량과 SOC 동시 추정이 가능하도록 하였다. 이를 통하여 배터리 충전 시 주기적인 배터리 용량 보정을 수행할 수 있다. 그리고, 방전 시에는 해당 용량으로 고정한 채 SOC를 추정하는, 배터리 관리 시스템에서 활용 가능한 추정 알고리즘을 제안하였다.