• 마이크로전자및패키징학회지
• /
• 제31권1호
• /
• pp.16-22
• /
• 2024

전기자동차와 신재생에너지에 관한 관심이 높아지면서 건설장비 산업분야에서도 리튬이온 배터리를 접목하려는 요구가 높아지고 있다. 건설중장비는 건설 현장의 다양한 작업으로 인해 전류 용량의 감소가 급속히 진행되기 때문에 SOC(State of Charge) 및 SOH(State of Health) 같은 배터리의 상태를 더욱 정확하게 추정할 필요가 있다. 본 논문에서는 SOC와 SOH를 동시에 추정이 가능한 적응제어 기법 기반 이중확장칼만필터(Dual Extended Kalman Filter, DEKF) 알고리즘을 이용하여 실제 측정데이터와의 오차를 비교하였다. 배터리 충전 상태 예측을 위해 배터리 셀을 완전 충전 후 0.2C-rate조건에서 SOC 5% 간격으로 OCV를 측정하였고, 배터리의 열화를 판단할 수 있는 건전성 지표 확보를 위해 다양한 C-rate(0.2, 0.3, 0.5, 1.0, 1.5C rate) 조건에서 50 Cycle 동안 노화 실험을 수행하였다. DEKF를 이용한 SOC 및 SOH 추정 오차는 C-rate이 커질수록 커지는 경향을 보였으며 특히 SOC 추정결과, 0.2, 0.5 및 1C-rate에서 6%이하로 나타남을 확인하였다. 또한 SOH 추정 결과는 0.2 와 0.3C-rate에서 각각 최대오차 1.0% 및 1.3% 이내로 좋은 성능을 보이는 것으로 확인하였다. 다만, C-rate가 0.5C-rate에서 1.5C-rate으로 증가함에 따라 추정오차도 1.5%에서 2%로 다소 증가하는 것을 확인할 수 있었으나, 모든 C-rate 조건에서 DEKF를 사용한 SOH의 추정 성능은 약 2% 이내인 것으로 나타났다.

• Journal of Electrical Engineering and Technology
• /
• 제13권5호
• /
• pp.1927-1934
• /
• 2018

In this paper, we studied the state of charge (SOC) estimation algorithm of a high-capacity lithium secondary battery for electric vehicles (EVs) considering temperature characteristics. Nonlinear characteristics of high-capacity lithium secondary batteries are represented by differential equations in the mathematical form and expressed by the state space equation through battery modeling to extract the characteristic parameters of the lithium secondary battery. Charging and discharging equipment were used to perform characteristic tests for the extraction of parameters of lithium secondary batteries at various temperatures. An extended Kalman filter (EKF) algorithm, a state observer, was used to estimate the state of the battery. The battery capacity and internal resistance of the high-capacity lithium secondary battery were investigated through battery modeling. The proposed modeling was applied to the battery pack for EVs to estimate the state of the battery. We confirmed the feasibility of the proposed study by comparing the estimated SOC values and the SOC values from the experiment. The proposed method using the EKF is expected to be highly applicable in estimating the state of the high-capacity rechargeable lithium battery pack for electric vehicles.

• 전력전자학회논문지
• /
• 제14권6호
• /
• pp.457-465
• /
• 2009

리튬계열 전지는 다른 이차전지에 비해 평균전압 및 에너지 밀도가 높으며 가볍고 수명이 긴 장점으로 인해 휴대용 전자기기에 폭넓게 사용되고 있으며, 특히 전기 자동차용으로 높은 수요가 예측되고 있다. 전기 자동차용 리튬 전지의 경우 운행 가능 거리의 정확한 계산이 요구되며, 또한 크랭킹이 불가능한 상태로 방전이 되지 않아야 하므로 충전상태에 대한 정확한 정보는 신뢰성 있는 운전을 위한 필수적인 요소가 된다. 본 논문에서는 AC 임피던스를 이용하여 리튬 폴리머 전지의 충전상태(SOC: State of Charge)를 추정하는 새로운 방법에 관해 제안한다. 제안된 방법에서는 주파수 별로 측정된 임피던스를 등가 임피던스 모델에 커브 피팅하여 파라미터를 추출하고, 추출된 파라미터를 이용하여 충전상태를 추정하였다. 제안된 방법에 의해 추출된 파라미터를 통해 리튬전지의 SOC 추정이 가능함을 증명하였고, 다수의 제조사에서 제작된 비슷한 용량의 리튬 폴리머 전지를 대상으로 한 실험을 통해 제안된 방법의 유용함을 검증하였다.

• 전력전자학회:학술대회논문집
• /
• 전력전자학회 2011년도 추계학술대회
• /
• pp.32-33
• /
• 2011

Recently, researches on SOC(State Of Charge) of batteries are being increased. Techniques of measuring the battery SOC is essential to researches on increasing cycle life of batteries and to electric vehicle battery charging systems. The surface charge phenomenon of lead storage batteries and the needs of SOC measuring techniques are considered. Features of SOC measuring techniques that have been recently developed are also considered.

• 한국철도학회:학술대회논문집
• /
• 한국철도학회 2011년도 정기총회 및 추계학술대회 논문집
• /
• pp.2329-2335
• /
• 2011

The Wireless low floor tram uses the energy more effectively than other systems with onboard battery system. But for this the SOC(state of charge) management of the battery system is required. This paper is focused on the SOC management strategy of battery system for propulsion in wireless low floor tram. For minimizing consumption energy, the SOC management strategy that maximizes the regeneration energy is studied. The SOC operating region is divided to overcome the limited life cycle pointed out as a disadvantage of battery system. And the effective energy management strategy of tram is suggested through the charge/discharge of the battery system according to tram status in catenary/catenary-free section.

• Journal of Power Electronics
• /
• 제10권6호
• /
• pp.769-776
• /
• 2010

The ultracapacitor module has recently been recast for use in hybrid energy storage systems (HESSs). As a result, accurate state-of-charge (SOC) estimation for an ultracapacitor module is as important as that of primary sources in order to be utilized efficiently in an energy storage system (ESS). However, while SOC estimation via the open-circuit voltage (OCV) method is generally used due to its linear characteristics compared with other ESSs, this method results in many errors in cases of highcurrent charging/discharging within a short time period. Accordingly, this paper introduces a dynamic SOC estimation algorithm that is capable of SOC compensation of an ultracapacitor module even when there is a current input and output. A cycle profile that simulates the operating conditions of a mild-HEV was applied to a vehicle simulator to verify the effectiveness of the proposed algorithm.

• Journal of Power Electronics
• /
• 제16권1호
• /
• pp.238-248
• /
• 2016

The state-of-charge (SOC) and state-of-health (SOH) estimation of batteries play important roles in managing batteries for automotive applications. However, an accurate state estimation of a battery is difficult to achieve because of certain factors, such as measurement noise, highly nonlinear characteristics, strong hysteresis phenomenon, and diffusion effect of batteries. In certain vehicular applications, such as idle stop-start systems (ISSs), significant errors in SOC/SOH estimation may lead to a failure in restarting a combustion engine after the shut-off period of the engine when the vehicle is at rest, such as at a traffic light. In this paper, a dual extended Kalman filter algorithm with a dynamic equivalent circuit model of a lead-acid battery is proposed to deal with this problem. The proposed algorithm adopts a battery model by taking into account the hysteresis phenomenon, diffusion effect, and parameter variations for accurate state estimations of the battery. The validity of the proposed algorithm is verified through experiments by using an absorbed glass mat valve-regulated lead-acid battery and a battery sensor cable for commercial ISS vehicles.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1998년도 하계학술대회 논문집 D
• /
• pp.1511-1513
• /
• 1998

The purpose of this study is to research and develop PEO/PVDF electrolytes and $LiMn_2O_4$ composite cathode for all-solid state lithium rechargeable battery. We investigated AC impedance response and charge/discharge cycling of $LiMn_2O_4$/SPE/Li cells. The cell resistance was decreased so much initial charge process from 0% SOC to 100% SOC. The radius of semicircle of $LiMn_2O_4$/SPE/Li cell was so much from initial state to 20th cycling. The discharge capacity of the $LiMn_2O_4$ composite cathode was 144mAh/g based on $LiMn_2O_4$.

• Journal of Power Electronics
• /
• 제16권2호
• /
• pp.643-653
• /
• 2016

The conventional methods used to evaluate battery state-of-charge (SOC) cannot accommodate the chemistry nonlinearities, measurement inaccuracies and parameter perturbations involved in estimation systems. In this paper, an impedance-based equivalent circuit model has been constructed with respect to a LiFePO₄ battery by approximating the electrochemical impedance spectrum (EIS) with RC circuits. The efficiencies of approximating the EIS with RC networks in different series-parallel forms are first discussed. Additionally, the typical hysteresis characteristic is modeled through an empirical approach. Subsequently, a methodology incorporating an H-infinity observer designated for open-circuit voltage (OCV) observation and a hysteresis model developed for OCV-SOC mapping is proposed. Thereafter, evaluation experiments under FUDS and UDDS test cycles are undertaken with varying temperatures and different current-sense bias. Experimental comparisons, in comparison with the EKF based method, indicate that the proposed SOC estimator is more effective and robust. Moreover, test results on a group of Li-ion batteries, from different manufacturers and of different chemistries, show that the proposed method has high generalization capability for all the three types of Li-ion batteries.

• 전력전자학회:학술대회논문집
• /
• 전력전자학회 2019년도 추계학술대회
• /
• pp.79-81
• /
• 2019

전기자동차(EV)뿐만 아니라 ESS(Energy Storage System) 등의 사용량이 증가하면서 리튬이온배터리의 중요성은 점점 커지고 있다. 리튬 이온 배터리의 정확한 상태를 추정하는 것은 배터리의 안전하고 신뢰성 있는 작동을 위해 매우 중요하다. 본 논문에서는 AEKF(Adaptive Extended Kalman Filter)를 이용한 배터리 파라미터와 충전상태(SOC, State of Charge)를 추정하고, 이를 활용하여 배터리의 건강상태(SOH, State of Health)를 추정하는 간단한 알고리즘을 제시한다. AEKF에 파라미터 값을 적용하여 SOC를 추정하고, 추정된 SOC값과 전류 적산을 이용하여 SOH를 추정한다. SOC 오차에 따른 SOH 추정 값의 편차는 SOC 연산 간격을 늘리고 가중치 필터를 적용하여 최소화시킴으로써 결과의 정확성을 향상했다. 다양한 자동차의 표준 주행 패턴을 적용한 실험을 통해 제안된 방법을 이용하여 얻어진 SOH 추정 결과는 RMSE(Root Mean Square Error) 1.428% 이내임을 검증하였다.