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Control-Oriented Multi-Physics Battery Modeling for Fast Discharging Near the Venting Threshold
Control-Oriented Multi-Physics Battery Modeling for Fast Discharging Near the Venting Threshold
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20260202105234
- ISBN
- 9798291567579
- DDC
- 620
- 저자명
- Tran, Vivian.
- 서명/저자
- Control-Oriented Multi-Physics Battery Modeling for Fast Discharging Near the Venting Threshold
- 발행사항
- [Sl] : University of Michigan, 2025
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2025
- 형태사항
- 142 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 87-02, Section: B.
- 주기사항
- Advisor: Siegel, Jason;Stefanopoulou, Anna.
- 학위논문주기
- Thesis (Ph.D.)--University of Michigan, 2025.
- 초록/해제
- 요약To improve lithium-ion battery (LIB) safety, predictive multiphysics algorithms are needed that can manage battery operation from normal to abnormal conditions. To address this gap, this dissertation develops control-oriented multiphysics LIB models that capture behavior from normal operation to first venting with minimal parameterization. Two reduced-order multiphysics models are developed by extending a normal operation model to simulate LIB pouch cell behaviors under high temperatures and currents, observed during external short circuit (ESC) experiments. This includes diffusion-limited electrical behaviors, cell expansion, gas generation, and first venting. The model emphasizes computational efficiency by coupling an equivalent circuit model (EqCM) with lumped thermal and cell venting phenomena. This parameterizable model is used to develop a model-predictive controller for safe and fast emergency discharge. Simulations show that imposing temperature and pressure constraints while maximizing discharge current allows a cell to discharge to 60% SOC in 2.5minutes while avoiding venting. However, the empirical EqCM cannot transition between normal and early failure conditions. To address this, a physics-based Single Particle Model with Electrolyte (SPMe) is used to capture the transition between normal and abnormal behavior, predicting venting timing within 10~seconds, consistent with experiments. A global sensitivity analysis of the pouch cell venting model highlights that uncertainties in preload, solid-electrolyte interphase (SEI) decomposition parameters, and temperature-dependent foam stiffness strongly influence the cell expansion force across temperature and age. The venting model shows that gas generation is highly sensitive to SEI stability and quantity, which are difficult to quantify in situ. To this end, a voltage fitting method is combined with a modeled electrode capacity distribution, where the standard deviation represents cell inhomogeneity. Inhomogeneity can accelerate degradation in localized regions, increasing the risks of failure. Taking into account inhomogeneity when characterizing degradation in cells with 50% capacity loss significantly reduced the differential voltage error throughout LIB life. These advances pave the way for an advanced state-of-health (SOH) estimation that accounts for inhomogeneity to help guide robust, aging-aware detection and mitigation strategies.
- 일반주제명
- Engineering
- 일반주제명
- Energy
- 일반주제명
- Mechanical engineering
- 키워드
- Battery safety
- 기타저자
- University of Michigan Mechanical Engineering
- 기본자료저록
- Dissertations Abstracts International. 87-02B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■00520260202105234
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■007cr#unu||||||||
■020 ▼a9798291567579
■035 ▼a(MiAaPQ)AAI32271924
■035 ▼a(MiAaPQ)umichrackham006505
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a620
■1001 ▼aTran, Vivian.
■24510▼aControl-Oriented Multi-Physics Battery Modeling for Fast Discharging Near the Venting Threshold
■260 ▼a[Sl]▼bUniversity of Michigan▼c2025
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2025
■300 ▼a142 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 87-02, Section: B.
■500 ▼aAdvisor: Siegel, Jason;Stefanopoulou, Anna.
■5021 ▼aThesis (Ph.D.)--University of Michigan, 2025.
■520 ▼aTo improve lithium-ion battery (LIB) safety, predictive multiphysics algorithms are needed that can manage battery operation from normal to abnormal conditions. To address this gap, this dissertation develops control-oriented multiphysics LIB models that capture behavior from normal operation to first venting with minimal parameterization. Two reduced-order multiphysics models are developed by extending a normal operation model to simulate LIB pouch cell behaviors under high temperatures and currents, observed during external short circuit (ESC) experiments. This includes diffusion-limited electrical behaviors, cell expansion, gas generation, and first venting. The model emphasizes computational efficiency by coupling an equivalent circuit model (EqCM) with lumped thermal and cell venting phenomena. This parameterizable model is used to develop a model-predictive controller for safe and fast emergency discharge. Simulations show that imposing temperature and pressure constraints while maximizing discharge current allows a cell to discharge to 60% SOC in 2.5minutes while avoiding venting. However, the empirical EqCM cannot transition between normal and early failure conditions. To address this, a physics-based Single Particle Model with Electrolyte (SPMe) is used to capture the transition between normal and abnormal behavior, predicting venting timing within 10~seconds, consistent with experiments. A global sensitivity analysis of the pouch cell venting model highlights that uncertainties in preload, solid-electrolyte interphase (SEI) decomposition parameters, and temperature-dependent foam stiffness strongly influence the cell expansion force across temperature and age. The venting model shows that gas generation is highly sensitive to SEI stability and quantity, which are difficult to quantify in situ. To this end, a voltage fitting method is combined with a modeled electrode capacity distribution, where the standard deviation represents cell inhomogeneity. Inhomogeneity can accelerate degradation in localized regions, increasing the risks of failure. Taking into account inhomogeneity when characterizing degradation in cells with 50% capacity loss significantly reduced the differential voltage error throughout LIB life. These advances pave the way for an advanced state-of-health (SOH) estimation that accounts for inhomogeneity to help guide robust, aging-aware detection and mitigation strategies.
■590 ▼aSchool code: 0127.
■650 4▼aEngineering
■650 4▼aEnergy
■650 4▼aMechanical engineering
■653 ▼alithium-ion battery
■653 ▼aBattery safety
■653 ▼aSolid-electrolyte interphase decomposition
■653 ▼aExternal short circuit experiments
■690 ▼a0537
■690 ▼a0791
■690 ▼a0548
■71020▼aUniversity of Michigan▼bMechanical Engineering.
■7730 ▼tDissertations Abstracts International▼g87-02B.
■790 ▼a0127
■791 ▼aPh.D.
■792 ▼a2025
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17359905▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
