Abstract:Accurate state of charge (SOC) estimation is essential for the battery management system (BMS). In engineering, inappropriate selection of equivalent circuit model (ECM) and model parameters is common for lithium-ion batteries. It can result in systematic errors (i.e., modeling errors) in the state-space equation, thus affecting the SOC estimation accuracy. Aiming at that, this paper proposes a self-calibration method to enhance SOC estimation. In the method, a novel state-space equation containing an unknown … Show more
“…For estimating the battery SoC, the coulomb counting method is used. It integrates the battery's current with time to calculate SOC, which is less complicated method, but limited by initial and cumulative errors [18] IV.…”
Section: Table (2): Piecewise Linear Relationship Of Soc-ocv At 25°cmentioning
Battery stacks based on lithium-ion (Li-ion) cells are used in many applications on a wide scale. Battery Management System (BMS) is description of the state of the Battery according to a specific input to get multiple outputs which could be used in system control. This paper introduces the application, and control of a DC/DC buck converter in charging the Li-ion batteries. The main parameter that can be estimated to describe the state of battery charging capacity is State of Charge (SoC). SoC is estimated based on the battery open circuit voltage (OCV), and the Coulomb's counting method. SoC limits are controlled to avoid overcharging the battery. Pulse Adjustment (PA) control technique is applied to control the switching of the of the DC/DC buck converter used to charge the Li-ion battery. So ensures constant charging current at the beginning of the charging process, within permissible limits. Hence avoid excessive heating that may degrade or damage the battery. MATLAB/Simulink tool is used for design verification. Simulation & Practical results were encouraging. A mobile application is designed to monitor the battery charging/discharging parameters.
“…For estimating the battery SoC, the coulomb counting method is used. It integrates the battery's current with time to calculate SOC, which is less complicated method, but limited by initial and cumulative errors [18] IV.…”
Section: Table (2): Piecewise Linear Relationship Of Soc-ocv At 25°cmentioning
Battery stacks based on lithium-ion (Li-ion) cells are used in many applications on a wide scale. Battery Management System (BMS) is description of the state of the Battery according to a specific input to get multiple outputs which could be used in system control. This paper introduces the application, and control of a DC/DC buck converter in charging the Li-ion batteries. The main parameter that can be estimated to describe the state of battery charging capacity is State of Charge (SoC). SoC is estimated based on the battery open circuit voltage (OCV), and the Coulomb's counting method. SoC limits are controlled to avoid overcharging the battery. Pulse Adjustment (PA) control technique is applied to control the switching of the of the DC/DC buck converter used to charge the Li-ion battery. So ensures constant charging current at the beginning of the charging process, within permissible limits. Hence avoid excessive heating that may degrade or damage the battery. MATLAB/Simulink tool is used for design verification. Simulation & Practical results were encouraging. A mobile application is designed to monitor the battery charging/discharging parameters.
Electric Vehicles (EVs) are a rapidly growing segment in India's automotive sector, with an expected 70\% growth by 2030. Lithium-ion (Li-ion) rechargeable batteries are favoured because of their high efficiency in power and energy delivery, along with fast charging, long lifespan, low self-discharge, and environmental friendliness. However, as a crucial subsystem in EVs, batteries are susceptible to faults arising from various factors. Li-ion battery faults can be categorized as internal or external. Internal faults stem from over-charging, over-discharging, overheating, acceleration and degradation processes, short circuits, and thermal runaway. External faults are caused by sensor malfunctions, cooling system failures, and cell connection problems. A Battery Management System (BMS) plays an essential role in regulating battery operation, monitoring its health status, and implementing fault diagnostic techniques. Fault diagnostic algorithms running on the BMS enable early or post-fault detection and control measures to minimize the consequences of faults, thereby ensuring battery safety and reliability. This paper reviews various internal and external battery fault diagnosis methods. In addition to battery fault detection, this work conducts a comparative analysis of optimization techniques for fault diagnosis, including Fuzzy Clustering, Long Short-Term Memory, Support Vector Machines, and Particle Swarm Optimization.
Bataryalar kimyasal yapılarına göre çeşitlilik gösterse de genel kullanım amaçları enerjiyi depo etmektir. Kullanıcı konforu ve bataryayı daha verimli kullanabilmek için batarya durumlarını tahmin etmek önemlidir. Bu çalışmada lityum bazlı bir bataryanın şarj durumu (SoC) ve sağlık durumu (SoH) Kalman filtresi yardımı ile kestirilmeye çalışılmıştır. Geliştirilen yöntem ile MATLAB programında oluşturulan bir batarya modelinin SoC ve SoH değerleri kestirilmiştir. MATLAB/Simulink’de var olan bataryanın SoC değeri önerilen yöntem ile kestirilmiş ve Simulink modelinin verdiği değer ile karşılaştırılmıştır. Yapılan benzetim çalışmalarında önerilen yöntem ile elde edilen değer ile Simulink modelinin verdiği değer arasındaki hata değerinin maksimum ±0.03 olduğu tespit edilmiştir. Benzer şekilde SoH kestirimi ile elde edilen değerin maksimum sapma miktarının ±0.03 olması beklenmektedir.
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