Date of Award
Doctor of Philosophy (PhD)
Dr. Ardalan Vahidi, Committee Chair
Dr. John R. Wagner
Dr. Mohammed Daqaq
Dr. Simona Onori
The rising rate of global energy demand alongside the dwindling fossil fuel resources has motivated research for alternative and sustainable solutions. Within this area of research, electrical energy storage systems are pivotal in applications including electriﬁed vehicles, renewable power generation, and electronic devices. The approach of this dissertation is to elucidate the bottlenecks of integrating supercapacitors and batteries in energy systems and propose solutions by the means of modeling, control, and experimental techniques. In the ﬁrst step, the supercapacitor cell is modeled in order to gain fundamental under-standing of its electrical and thermal dynamics. The dependence of electrical parameters on state of charge (SOC), current direction and magnitude (20-200 A), and temperatures ranging from -40 °C to 60 °C was embedded in this computationally efﬁcient model. The coupled electro-thermal model was parameterized using speciﬁcally designed temporal experiments and then validated by the application of real world duty cycles. Driving range is one of the major challenges of electric vehicles compared to combustion vehicles. In order to shed light on the beneﬁts of hybridizing a lead-acid driven electric vehicle via supercapacitors, a model was parameterized for the lead-acid battery and combined with the model already developed for the supercapacitor, to build the hybrid battery-supercapacitor model. A hard-ware in the loop (HIL) setup consisting of a custom built DC/DC converter, micro-controller (µC) to implement the power management strategy, 12 V lead-acid battery, and a 16.2 V supercapacitor module was built to perform the validation experiments. Charging electrical energy storage systems in an efﬁcient and quick manner, motivated to solve an optimal control problem with the objective of maximizing the charging efﬁciency for supercapacitors, lead-acid, and lithium ion batteries. Pontryagins minimum principle was used to solve the problems analytically. Efﬁciency analysis for constant power (CP) and optimal charging strategies under different charging times (slow and fast) was performed. In case of the lithium ion battery, the model included the electronic as well as polarization resistance. Furthermore, in order to investigate the inﬂuence of temperature on the internal resistance of the lithium ion battery, the optimal charging problem for a three state electro-thermal model was solved using dynamic programming (DP). The ability to charge electric vehicles is a pace equivalent to fueling a gasoline car will be a game changer in the widespread acceptability and feasibility of the electric vehicles. Motivated by the knowledge gained from the optimal charging study, the challenges facing the fast charging of lithium ion batteries are investigated. In this context, the suitable models for the study of fast charging, high rate anode materials, and different charging strategies are studied. The side effects of fast charging such as lithium plating and mechanical failure are also discussed. This dissertation has targeted some of the most challenging questions in the ﬁeld of elec-trical energy storage systems and the reported results are applicable to a wide range of applications such as in electronic gadgets, medical devices, electricity grid, and electric vehicles.
Parvini, Yasha, "Modeling, Hybridization, and Optimal Charging of Electrical Energy Storage Systems" (2016). All Dissertations. 1709.