Ciencias Exactas y Ciencias de la Salud
Permanent URI for this collectionhttps://hdl.handle.net/11285/551039
Pertenecen a esta colección Tesis y Trabajos de grado de las Maestrías correspondientes a las Escuelas de Ingeniería y Ciencias así como a Medicina y Ciencias de la Salud.
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- Electric vehicle’s battery cell modeling and state of charge sstimation(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-12) Barragán Hernández, Allen Uriel; Tudón Martínez, Juan Carlos; emipsanchez; Martinez Molina, John Jairo; Lozoya Santos, Jorge Jesús de; School of Engineering and Sciences; Campus MonterreyThe rapid growth in electric vehicle (EV) adoption underscores the necessity for precise battery management systems (BMS) to ensure safety, efficiency, and longevity of lithium-ion batteries, the leading technology in EV battery packs. As EV technology evolves, the need for accurate State of Charge (SOC) estimation becomes increasingly critical, influencing battery performance, lifespan, and operational safety. Despite advancements, current SOC estimation models struggle to predict SOC accurately under diverse real world conditions, often due to simplifying assumptions or controlled testing environments. Existing models fail to capture dynamic voltage behaviors influenced by charge-discharge cycles, leading to potential inaccuracies in SOC prediction under practical scenarios. This research develops a robust SOC estimation model for EV batteries, integrating advanced battery modeling and Extended Kalman Filter (EKF) methodologies. The study seeks to improve SOC estimation accuracy and reliability, addressing the complex and nonlinear behaviors of lithium-ion batteries in varying operating conditions. Three distinct battery models, (one-state, two-state, and three-state model), each with increasing complexity and fidelity in SOC prediction are employed in this research. Using real world battery performance data, these models are refined through EKF implementation, allowing real-time SOC estimation under variable conditions. The study reveals that model complexity directly correlates with SOC estimation accuracy. The three-state model, while computationally demanding, achieves the highest accuracy The two-state model strikes a balance between accuracy and resource efficiency. Conversely, the one-state model is appropriate for low-stakes applications that do not require high SOC precision. Results highlight that different applications may require varying levels of model complexity to align with their accuracy and resource demands.
- Development of a DC-DC converter-based balancing system for Lithium-ion battery cells based on State of Power reference(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2021-06) Martínez Barrón, Abraham Alberto; Escobar Valderrama, Gerardo; puemcuervo; Valdez, Jesús; Escuela de Ingeniería y Ciencias; Campus Monterrey; Schacht, RicardoIn recent years, Li-ion battery packs have become a major component of new technologies like energy storage systems and electric vehicles. Due to the safety limitations inherent to Li-ion battery cells, these packs need to be operated under precise voltage, temperature, and current conditions, which are variables supervised by a BMS. Depending on the application, battery packs are often comprised of several individual cells. However, each battery cell has slight variations, which can lead to performance and service life issues. This problem is addressed by implementing different types of balancing systems. Nevertheless, current methodologies face several limitations, such as a low energy efficiency for passive systems and high costs and complexity for active circuits. A new balancing system, consisting of the combination of a modular active DC-DC converter-based topology, a multi-factor balancing algorithm, and a control strategy for balancing current based on SoP, is developed in this research project. The resulting system can expand the runtime of the battery pack, as the energy is distributed better among cells. Besides, the energy that can be injected into the battery pack during charging has also been increased, as the excess of energy is moved from overcharged cells to the rest before anyone of them reaches its top voltage.
