Integrated Li-Ion Ultracapacitor with Lead Acid Battery for Vehicular Start-Stop

Advancements in automobile manufacturing aim at improving the driving experience at every level possible. One improvement aspect is increasing gas efficiency via hybridization, which can be achieved by introducing a feature called start-stop. This feature automatically switches the internal combustion engine off when it idles and switches it back on when it is time to resume driving. This application has been proven to reduce the amount of gas consumption and emission of greenhouse effect gases in the atmosphere. However, the repeated cranking of the engine puts a large amount of stress on the lead acid battery required to perform the cranking, which effectively reduces its life span. This dissertation presents a hybrid energy storage system assembled from a lead acid battery and an ultracapacitor module connected in parallel. The Li-ion ultracapacitor was tested and modeled to predict its behavior when connected in a system requiring pulsed power such as the one proposed. Both test and simulation results show that the proposed hybrid design significantly reduces the cranking loading and stress on the battery. The ultracapacitor module can take the majority of the cranking current, effectively reducing the stress on the battery. The amount of cranking current provided by the ultracapacitor can be easily controlled via controlling the resistance of the cable connected directly between the ultracapacitor module and the car circuitry

Real-Time Power Management of A Fuel Cell/Ultracapacitor Hybrid

This thesis presents the system architecture design, system integration methodology, and real-time control of a fuel cell/ultracapacitor hybrid power system. The main objective is for the hybrid system to respond to real-world fluctuations in power without negatively impacting fuel cell life. A Proton Exchange Membrane (PEM) Fuel Cell is an electrochemical device which converts the chemical energy of pure hydrogen into electricity through a chemical reaction with oxygen. The high conversion efficiency, zero harmful emissions, high power-to-weight ratio, scalability, and low temperature operation make PEM fuel cells very attractive for stationary and portable power applications. However, fuel cells are limited in responding to fast transients in power demand, moreover power fluctuations have negative impact on fuel cell durability. This motivates the use of a supplementary energy storage device to assist the fuel cell by buffering sharp transients in power demand. The high power density, long cycle life, and efficiency of ultracapacitors make them an ideal solution for such auxiliary energy storage in a hybrid fuel cell system. The power management strategy that determines the power split between the fuel cell and ultracapacitor is key to the power following capability, long-term performance, and life-time of the fuel cell. In this thesis, a rule-based and a model predictive control strategy are designed, implemented and evaluated for power management of a fuel cell/ultracapacitor hybrid. The high-level control objectives are to respond to rapid variations in load while minimizing damaging fluctuations in fuel cell current and maintaining ultracapacitor charge (or voltage) within allowable bounds. An experimental test stand was created to evaluate the performance of the controllers. The test stand connects the fuel cell and ultracapacitor to an electronic load through two dc/dc converters, which provide two degrees of freedom, enabling independent low-level control of the DC BUS voltage and the current split between the fuel cell and ultracapacitor. Experiments show that both rule-based and model predictive power management strategies can be tuned to meet both high and low-level control objectives for a given power demand profile. However, the capability to explicitly enforce the constraints in model predictive scheme and its predictive nature in meeting power demands enables a more systematic design and results in general in smoother performance

Management of Distributed Energy Storage Systems for Provisioning of Power Network Services

Because of environmentally friendly reasons and advanced technological development, a significant number of renewable energy sources (RESs) have been integrated into existing power networks. The increase in penetration and the uneven allocation of the RESs and load demands can lead to power quality issues and system instability in the power networks. Moreover, high penetration of the RESs can also cause low inertia due to a lack of rotational machines, leading to frequency instability. Consequently, the resilience, stability, and power quality of the power networks become exacerbated. This thesis proposes and develops new strategies for energy storage (ES) systems distributed in power networks for compensating for unbalanced active powers and supply-demand mismatches and improving power quality while taking the constraints of the ES into consideration. The thesis is mainly divided into two parts. In the first part, unbalanced active powers and supply-demand mismatch, caused by uneven allocation and distribution of rooftop PV units and load demands, are compensated by employing the distributed ES systems using novel frameworks based on distributed control systems and deep reinforcement learning approaches. There have been limited studies using distributed battery ES systems to mitigate the unbalanced active powers in three-phase four-wire and grounded power networks. Distributed control strategies are proposed to compensate for the unbalanced conditions. To group households in the same phase into the same cluster, algorithms based on feature states and labelled phase data are applied. Within each cluster, distributed dynamic active power balancing strategies are developed to control phase active powers to be close to the reference average phase power. Thus, phase active powers become balanced. To alleviate the supply-demand mismatch caused by high PV generation, a distributed active power control system is developed. The strategy consists of supply-demand mismatch and battery SoC balancing. Control parameters are designed by considering Hurwitz matrices and Lyapunov theory. The distributed ES systems can minimise the total mismatch of power generation and consumption so that reverse power flowing back to the main is decreased. Thus, voltage rise and voltage fluctuation are reduced. Furthermore, as a model-free approach, new frameworks based on Markov decision processes and Markov games are developed to compensate for unbalanced active powers. The frameworks require only proper design of states, action and reward functions, training, and testing with real data of PV generations and load demands. Dynamic models and control parameter designs are no longer required. The developed frameworks are then solved using the DDPG and MADDPG algorithms. In the second part, the distributed ES systems are employed to improve frequency, inertia, voltage, and active power allocation in both islanded AC and DC microgrids by novel decentralized control strategies. In an islanded DC datacentre microgrid, a novel decentralized control of heterogeneous ES systems is proposed. High- and low frequency components of datacentre loads are shared by ultracapacitors and batteries using virtual capacitive and virtual resistance droop controllers, respectively. A decentralized SoC balancing control is proposed to balance battery SoCs to a common value. The stability model ensures the ES devices operate within predefined limits. In an isolated AC microgrid, decentralized frequency control of distributed battery ES systems is proposed. The strategy includes adaptive frequency droop control based on current battery SoCs, virtual inertia control to improve frequency nadir and frequency restoration control to restore system frequency to its nominal value without being dependent on communication infrastructure. A small-signal model of the proposed strategy is developed for calculating control parameters. The proposed strategies in this thesis are verified using MATLAB/Simulink with Reinforcement Learning and Deep Learning Toolboxes and RTDS Technologies' real-time digital simulator with accurate power networks, switching levels of power electronic converters, and a nonlinear battery model

Power Interface Design and System Stability Analysis for 400 V DC-Powered Data Centers

The demands of high performance cloud computation and internet services have increased in recent decades. These demands have driven the expansion of existing data centers and the construction of new data centers. The high costs of data center downtime are pushing designers to provide high reliability power supplies. Thus, there are significant research questions and challenges to design efficient and environmentally friendly data centers with address increasing energy prices and distributed energy developments. This dissertation work aims to study and investigate the suitable technologies of power interface and system level configuration for high efficiency and reliable data centers. A 400 V DC-powered data center integrated with solar power and hybrid energy storage is proposed to reduce the power loss and cable cost in data centers. A cascaded totem-pole bridgeless PFC converter to convert grid ac voltage to the 400 V dc voltage is proposed in this work. Three main control strategies are developed for the power converters. First, a model predictive control is developed for the cascaded totem-pole bridgeless PFC converter. This control provides stable transient performance and high power efficiency. Second, a power loss model based dual-phase-shift control is applied for the efficiency improvement of dual-active bridge converter. Third, an optimized maximum power point tracking (MPPT) control for solar power and a hybrid energy storage unit (HESU) control are given in this research work. The HESU consists of battery and ultracapacitor packs. The ultracapacitor can improve the battery lifetime and reduce any transients affecting grid side operation. The large signal model of a typical solar power integrated datacenter is built to analyze the system stability with various conditions. The MATLAB/Simulink™-based simulations are used to identify the stable region of the data center power supply. This can help to analyze the sensitivity of the circuit parameters, which include the cable inductance, resistance, and dc bus capacitance. This work analyzes the system dynamic response under different operating conditions to determine the stability of the dc bus voltage. The system stability under different percentages of solar power and hybrid energy storage integrated in the data center are also investigated

Power Interface Design and System Stability Analysis for 400 V DC-Powered Data Centers

The demands of high performance cloud computation and internet services have increased in recent decades. These demands have driven the expansion of existing data centers and the construction of new data centers. The high costs of data center downtime are pushing designers to provide high reliability power supplies. Thus, there are significant research questions and challenges to design efficient and environmentally friendly data centers with address increasing energy prices and distributed energy developments. This dissertation work aims to study and investigate the suitable technologies of power interface and system level configuration for high efficiency and reliable data centers. A 400 V DC-powered data center integrated with solar power and hybrid energy storage is proposed to reduce the power loss and cable cost in data centers. A cascaded totem-pole bridgeless PFC converter to convert grid ac voltage to the 400 V dc voltage is proposed in this work. Three main control strategies are developed for the power converters. First, a model predictive control is developed for the cascaded totem-pole bridgeless PFC converter. This control provides stable transient performance and high power efficiency. Second, a power loss model based dual-phase-shift control is applied for the efficiency improvement of dual-active bridge converter. Third, an optimized maximum power point tracking (MPPT) control for solar power and a hybrid energy storage unit (HESU) control are given in this research work. The HESU consists of battery and ultracapacitor packs. The ultracapacitor can improve the battery lifetime and reduce any transients affecting grid side operation. The large signal model of a typical solar power integrated datacenter is built to analyze the system stability with various conditions. The MATLAB/Simulink™-based simulations are used to identify the stable region of the data center power supply. This can help to analyze the sensitivity of the circuit parameters, which include the cable inductance, resistance, and dc bus capacitance. This work analyzes the system dynamic response under different operating conditions to determine the stability of the dc bus voltage. The system stability under different percentages of solar power and hybrid energy storage integrated in the data center are also investigated

High-density And High-efficiency Soft Switching Modular Bi-directional Dc-dc Converter For Hybrid Electric Vehicles

This dissertation1 presents the design of a high-density and high-efficiency soft-switching bi-directional DC-DC converter for hybrid-electric vehicles. The converter operates in a new bidirectional interleaved variable-frequency quasi-square-wave (QSW) mode, which enables high efficiency, high switching frequency, and high power-density. The converter presented utilizes a new variable frequency interleaving approach which allows for each module to operate in an interleaved position while allowing for tolerance in inductance and snubber capacitor values. The variable frequency interleaved soft-switching operation paired with a high-density nanocrystalline inductor and high-density system structure results in a very high performance converter, well exceeding that of the current technology. The developed converter is intended to achieve three specific performance goals: high conversion efficiency, high power density, and operation with 100 °C coolant. Two markedly different converter prototype designs are presented, one converter using evaporative spray cooling to cool the switching devices, with the second converter using a more traditional coldplate design to cool the switching devices. The 200 kW (25 kW per module) prototype converters exhibited power density greater than 8 kilowatts/liter (kW/L), and peak efficiency over 98%, while operating with 100 °C coolan

Damping Optimum-Based Design of Control Strategy Suitable for Battery/Ultracapacitor Electric Vehicles

This contribution outlines the design of electric vehicle direct-current (DC) bus control system supplied by a battery/ultracapacitor hybrid energy storage system, and its coordination with the fully electrified vehicle driveline control system. The control strategy features an upper-level DC bus voltage feedback controller and a direct load compensator for stiff tracking of variable (speed-dependent) voltage target. The inner control level, comprising dedicated battery and ultracapacitor current controllers, is commanded by an intermediate-level control scheme which dynamically distributes the upper-level current command between the ultracapacitor and the battery energy storage systems. The feedback control system is designed and analytical expressions for feedback controller parameters are obtained by using the damping optimum criterion. The proposed methodology is verified by means of simulations and experimentally for different realistic operating regimes, including electric vehicle DC bus load step change, hybrid energy storage system charging/discharging, and electric vehicle driveline subject to New European Driving Cycle (NEDC), Urban Driving Dynamometer Schedule (UDDS), New York Certification Cycle (NYCC) and California Unified Cycle (LA92), as well as for abrupt acceleration/deceleration regimes

Lithium-Ion Ultracapacitor Energy Storage Integrated with a Variable Speed Wind Turbine for Improved Power Conversion Control

The energy of wind has been increasingly used for electric power generation worldwide due to its availability and ecologically sustainability. Utilization of wind energy in modern power systems creates many technical and economical challenges that need to be addressed for successful large scale wind energy integration. Variations in wind velocity result in variations of output power produced by wind turbines. Variable power output becomes a challenge as the amount of output power of the wind turbines integrated into power systems increases. Large power variations cause voltage and frequency deviations from nominal values that may lead to activation of relay protective equipment, which may result in disconnection of the wind turbines from the grid. Particularly community wind power systems, where only one or a few wind turbines supply loads through a weak grid such as distribution network, are sensitive to supply disturbances. While a majority of power produced in modern power systems comes from synchronous generators that have large inertias and whose control systems can compensate for slow power variations in the system, faster power variations at the scale of fraction of a second to the tens of seconds can seriously reduce reliability of power system operation. Energy storage integrated with wind turbines can address this challenge. In this dissertation, lithium-ion ultracapacitors are investigated as a potential solution for filtering power variations at the scale of tens of seconds. Another class of issues related to utilization of wind energy is related to economical operation of wind energy conversion systems. Wind speed variations create large mechanical loads on wind turbine components, which lead to their early failures. One of the most critical components of a wind turbine is a gearbox that mechanically couples turbine rotor and generator. Gearboxes are exposed to large mechanical load variations which lead to their early failures and increased cost of wind turbine operation and maintenance. This dissertation proposes a new critical load reduction strategy that removes mechanical load components that are the most dangerous in terms of harmful effect they have on a gearbox, resulting in more reliable operation of a wind turbine