In this study, the thermal behavior and performance of pouch type Lithium-Ion Batteries (LIB) which are used in Hybrid Electric Vehicles (HEVs) and Electrical Vehicles (EVs) has been investigated at different discharge rates based on numerical simulations. Numerical simulation was performed through a traditional software package using the dual potential Multi-Scale Multi-Dimensional (MSMD) battery model to analyze the cell discharge behavior and investigate its thermal performance. When the battery load is increased, non-uniform thermal distribution and temperature rise has been observed. Non-uniform thermal distribution causes loss of capacity and performance in the battery. Therefore, an accurate and effective cooling system is required to eliminate non-uniform temperature distribution. This study is a preliminary preparation for cooling system design.

Energy storage systems (ESS) are indispensable in daily life and have two types that can offer high energy and high power density. Hybrid energy storage systems (HESS) are obtained by combining two or more energy storage units to benefit both types. Energy management systems (EMS) are essential in ensuring the reliability, high performance, and efficiency of HESS. One of the most critical parameters for EMS is the battery state of health (SoH). Continuous monitoring of the SoH provides essential information regarding the system status, detects unusual performance degradations and enables planned maintenance, prevents system failures, helps keep efficiency at a consistently high level, and helps ensure energy security by reducing downtime. The SoH parameter depends on parameters such as depth of discharge (DoD), charge and discharge rate (C-rate), and temperature. Optimal values of these parameters directly affect the lifetime and operating performance of the battery. The proposed adaptive energy management system (AEMS) uses the SoH parameter of the battery as the control input. It provides optimal control by dynamically updating the C-rate and DoD parameters. In addition, the supercapacitor integrated into the system with filter-based power separation prevents deep discharge of the batteries. Under the proposed AEMS control, HESS has been observed to generate 6.31% more energy than a system relying solely on batteries. This beneficial relationship between supercapacitors and batteries efficiently managed by AEMS opens new possibilities for advanced energy management in applications ranging from electric vehicles to renewable energy storage systems.

Bu çalışmada iki farklı metot kullanılarak PID parametre ayarlaması yapılmıştır. İlk olarak Doğrusal Karesel Düzenleyici (LQR) yaklaşımı kullanılarak maliyet fonksiyonu minimize edilmiş ve optimal parametreler elde edilerek LQR tabanlı PID denetleyici tasarlanmıştır. Ardından LQR maliyet fonksiyonunun minimizasyonu için Genetik Algoritma (GA) kullanılmış ve GA tabanlı PID denetleyici tasarlanmıştır. Tasarlanan PID denetleyiciler bir sıvı seviye kontrol sisteminde benzetimsel ve deneysel olarak test edilmiş ve performans karşılaştırmaları yapılmıştır. Deneysel sonuçlar, GA tabanlı PID'nin performansının LQR tabanlı PID'den performans indisleri açısından daha başarılı olduğunu göstermektedir. GA Tabanlı PID için normalize edilmiş ITSE indisi 0.6479 ile daha başarılı performans sergilemiştir.