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Modeling the performance of lithium-ion batteries for electric vehicle and energy storage applications

  • 이동철 (Dongcheul Lee, 아주대학교 일반대학원)

초록/요약

Lithium-ion batteries (LIBs) with the advantages of high energy, power density, and energy efficiency are a key power source for sustainable development in the field of mobility systems and electrical energy storage in climate emergencies. The performance of LIBs is affected by factors such as operating and environmental conditions and duration of use, which may reduce their lifespan and cause safety issues. Therefore, it is important to operate the battery system appropriately by calculating the electrical and thermal behavior and cell deviations of the LIB in an environment considering actual applications, such as electric vehicles (EVs) and energy storage systems (ESSs). LIB performance modeling can play an important role in battery management system algorithm strategies for EVs and ESS applications. The first part of this thesis describes a methodology for quantitatively devising a fast charge protocol to prevent lithium plating in an LIB cell. A lithium plating line was derived by detecting the voltage plateau that occurred during charging with a high current using differential voltage analysis (DVA). To account for the safety effects at a certain margin from the lithium plating line during fast charging, a novel index was expressed as a margin of safety (MS). Two-dimensional modeling was performed to predict the charge curves and thermal distributions of the LIB cell under various conditions according to the margin of safety. To validate the modeling approach in the design of the fast-charge protocol, cycling tests were performed under five fast-charge protocols and discharge. The higher the MS of the fast charge protocol, the better the performance and lifetime impact of the LIB cell. The second part of this thesis describes a methodology to estimate the combined effects of cyclable lithium loss and electrolyte depletion on the capacity and discharge power fading of LIBs. An LIB cell based on LiNi0.6Co0.2Mn0.2O2 (NCM622) was used to model the discharge behavior in multiple degradation modes. The discharge voltages for nine different levels of cyclable lithium loss and electrolyte depletion were experimentally measured. When there was no cyclable lithium loss, 50% electrolyte depletion resulted in a 5% reduction in discharge capacity at 0.05 C discharge rate, while when it was coupled with 30% cyclable lithium loss, it resulted in a 46% reduction. A 50% electrolyte depletion with no cyclable lithium loss caused a 1% reduction in discharge power during 0.5 C discharge at a state of charge (SOC) level of 0.8, while it resulted in a 13% reduction when it was coupled with 30% cyclable lithium loss. The modeling results obtained using the one-dimensional finite element method were compared with the experimental data. The modeling methods are justified by the high degree of concordance between the predicted and experimental values. Using the validated modeling methodology, the discharge capacity and usable discharge power can be estimated effectively under various combined degradation modes of cyclable lithium loss and electrolyte depletion in LIB cells. The final part of this thesis describes a methodology that considers the effect of cell variation on the performance of LIB modules in energy storage applications to improve the reliability of the power quality of energy storage devices and the efficiency of energy systems. Ohm’s law and the law of conservation of charge were employed as governing equations to estimate the discharge behavior of a single strand composed of two LIB cells connected in parallel based on the polarization properties of the electrode. Using the modeling parameters of a single strand, the particle swarm optimization algorithm was adopted to predict the discharge capacity and internal resistance distribution of 14 strands connected in series. Based on the model of the LIB strand to predict the discharge behavior, the effect of cell variation on the deviation of the discharge termination voltage and the depth of discharge imbalance was modeled. The validity of this model was confirmed by comparing the experimental data with the modeling results.

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초록/요약

리튬이온전지는 높은 에너지 밀도, 고출력 및 에너지 효율이 높다는 장점이 있어 기후 비상사태를 직면한 요즘 모빌리티 시스템 및 전기에너지 저장 분야에서 지속가능한 발전을 위한 핵심 동력원이다. 리튬이온전지의 성능은 운영 및 환경 조건, 사용기간 등의 요인에 따라 변화될 수 있어 장기수명 및 안전성 문제가 발생할 수 있다. 따라서 전기자동차, 에너지저장장치의 실제 운영조건을 고려한 환경에서 리튬이온전지의 전기적 및 열적 거동, 셀 간 편차 등을 계산해 배터리 시스템을 적절하게 운용하는 것이 중요하다. 리튬이온전지의 성능 모델링은 전기자동차 및 에너지저장시스템 애플리케이션에서 배터리 관리 시스템의 운용 전략에 중요한 역할을 할 수 있다. 첫 번째는 리튬 플레이팅을 방지하기 위해 급속충전 프로토콜을 정량적으로 고안하는 방법론을 설명한다. 차동 전압 분석(differential voltage analysis)에 기반하여 높은 전류로 충전했을 때 전압 곡선의 변곡점을 구하여 리튬 플레이팅 라인을 도출했다. 급속충전시 리튬 플레이팅 라인으로부터 일정한 마진에서의 안전효과를 설명하기 위해 새로운 지수를 MS(margin of safety)를 개발하였다. 안전 마진에 따른 리튬이온전지의 충전 전압과 열 분포를 예측하기 위해 2차원 모델링을 수행했다. 급속충전 프로토콜 설계를 위한 모델링 접근 방식을 검증하기 위해 5가지 급속충전 프로토콜 및 방전 하에서 사이클링 시험을 수행했다. 두 번째는 LiNi0.6Co0.2Mn0.2O2 리튬이온전지의 용량 및 방전 출력 감소에 대한 비가역적인 리튬 손실과 전해질 고갈의 결합된 효과를 추정하는 모델링 방법론이다. 1차원 유한요소법에 기반한 리튬이온전지를 사용하여 9가지 다른 수준의 비가역적인 리튬 손실 및 전해질 고갈에 대한 방전 성능을 모델링했다. 모델링 방법론의 타당성은 모델링결과와 실험값을 비교하여 검증했다. 마지막은 에너지 저장 장치의 전력 품질의 신뢰성과 에너지 시스템의 효율성을 향상시키기 위해 셀 간 편차가 리튬이온전지 모듈의 성능에 미치는 영향을 고려하는 모델링 방법론에 대해 설명한다. 리튬이온전지 셀이 2개로 구성된 단일 가닥의 모델링 파라미터를 사용하여 직렬로 연결된 14개 가닥의 방전 용량 및 내부 저항 분포를 예측하기 위해 입자 군집 최적화(particle swarm optimization) 알고리즘을 채택했다. 방전 거동을 예측하기 위한 리튬이온전지 가닥의 성능 모델을 기반으로 방전 전압, 방전 깊이(depth of discharge)의 불균형에 대한 셀 간 편차의 영향을 계산했다. 실험 데이터와 모델링 결과를 비교하여 모델의 타당성을 확인하였다.

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목차


Chapter 1. Introduction 1
1.1. Lithium-ion battery 1
1.2. Fast charge of LIB 5
1.3. Aging mechanism of LIB 6
1.4. Cell variation of LIB module 8
1.5. Dissertation outline 9
Chapter 2. Modeling the effect of Fast Charge Protocols to Prevent Lithium Plating on the Performance in a LIB 11
2.1. Introduction 11
2.2. Mathematical model 15
2.3. Results and Discussion 22
2.3.1 Fast Charge Protocols to Prevent Lithium Plating 22
2.3.2 Modeling of Fast Charge Performance of LIB Cell 28
2.3.3 Charge Performance and Lifetime Performance of LIB Cell 36
Chapter 3. Modeling the Combined Effects of Cyclable Lithium Loss and Electrolyte Depletion on the Performance Fades of a LIB 42
3.1. Introduction 42
3.2. Mathematical model 45
3.3. Experimental Section 50
3.4. Results and Discussion 53
3.4.1 Model Validation for LIB Cell 53
3.4.2 Modeling of Performance Fades of LIB Cell 61
Chapter 4. Modeling the Effect of Cell Variation on the Performance of a LIB Module 68
4.1. Introduction 68
4.2. Mathematical model 71
4.3. Experimental section 77
4.4. Results and Discussion 78
4.4.1 Model Validation for LIB Strand 78
4.4.2 Model Validation for LIB Module 85
4.4.3 Modeling of LIB Module Performance 92
Chapter 5. Summary and conclusions 99
Bibliography 102
Appendix A. Nomenclature 112
Appendix B. Battery glossary 117
국 문 초 록 119

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