Energy Management of a Battery-Ultracapacitor Hybrid Energy Storage System in Electric Vehicles

Electric vehicle (EV) batteries tend to have accelerated degradation due to high peak power and harsh charging/discharging cycles during acceleration and deceleration periods, particularly in urban driving conditions. An oversized energy storage system (ESS) can meet the high power demands; however, it suffers from increased size, volume and cost. In order to reduce the overall ESS size and extend battery cycle life, a battery-ultracapacitor (UC) hybrid energy storage system (HESS) has been considered as an alternative solution. In this work, we investigate the optimized configuration, design, and energy management of a battery-UC HESS. One of the major challenges in a HESS is to design an energy management controller for real-time implementation that can yield good power split performance. We present the methodologies and solutions to this problem in a battery-UC HESS with a DC-DC converter interfacing with the UC and the battery. In particular, a multi-objective optimization problem is formulated to optimize the power split in order to prolong the battery lifetime and to reduce the HESS power losses. This optimization problem is numerically solved for standard drive cycle datasets using Dynamic Programming (DP). Trained using the DP optimal results, an effective real-time implementation of the optimal power split is realized based on Neural Network (NN). This proposed online energy management controller is applied to a midsize EV model with a 360V/34kWh battery pack and a 270V/203Wh UC pack. The proposed online energy management controller effectively splits the load demand with high power efficiency and also effectively reduces the battery peak current. More importantly, a 38V-385Wh battery and a 16V-2.06Wh UC HESS hardware prototype and a real-time experiment platform has been developed. The real-time experiment results have successfully validated the real-time implementation feasibility and effectiveness of the real-time controller design for the battery-UC HESS. A battery State-of-Health (SoH) estimation model is developed as a performance metric to evaluate the battery cycle life extension effect. It is estimated that the proposed online energy management controller can extend the battery cycle life by over 60%.

INVESTIGATION OF MAGNESIUM ION CHARGE STORAGE MECHANISM IN MANGANESE DIOXIDE

Magnesium (Mg) battery is considered as a promising candidate for the next generation battery technology that could potentially replace the current lithium (Li)-ion batteries due to the following factors. Magnesium possesses a higher volumetric capacity than commercialized Li-ion battery anode materials. Additionally, the low cost and high abundance of Mg compared to Li makes Mg batteries even more attractive. Moreover, unlike metallic Li anodes which have a tendency to develop a dendritic structure on the surface upon the cycling of the battery, Mg metal is known to be free from such a hazardous phenomenon. Due to these merits of Mg as an anode, the topic of rechargea¬ble Mg batteries has attracted considerable attention among researchers in the last few decades. However, the aforementioned advantages of Mg batteries have not been fully utilized due to the serious kinetic limitation of Mg2+ diffusion process in many hosting compounds which is believed to be due to a strong electrostatic interaction between divalent Mg2+ ions and hosting matrix. This serious kinetic hindrance is directly related to the lack of cathode materials for Mg battery that provide comparable electrochemical performances to that of Li-based system. Manganese oxide (MnO2) is one of the most well studied electrode materials due to its excellent electrochemical properties, including high Li+ ion capacity and relatively high operating voltage (i.e., ~ 4 V vs. Li/Li+ for LiMn2O4 and ~ 3.2 V vs. Mg/Mg2+). However, unlike the good electrochemical properties of MnO2 realized in Li-based systems, rather poor electrochemical performances have been reported in Mg based systems, particularly with low capacity and poor cycling performances. While the origin of the observed poor performances is believed to be due to the aforementioned strong ionic interaction between the Mg2+ ions and MnO2 lattice resulting in a limited diffusion of Mg2+ ions in MnO2, very little has been explored regarding the charge storage mechanism of MnO2 with divalent Mg2+ ions. This dissertation investigates the charge storage mechanism of MnO2, focusing on the insertion behaviors of divalent Mg2+ ions and exploring the origins of the limited Mg2+ insertion behavior in MnO2. It is found that the limited Mg2+ capacity in MnO2 can be significantly improved by introducing water molecules in the Mg electrolyte system, where the water molecules effectively mitigated the kinetic hindrance of Mg2+ insertion process. The combination of nanostructured MnO2 electrode and water effect provides a synergic effect demonstrating further enhanced Mg2+ insertion capability. Furthermore, it is demonstrated in this study that pre-cycling MnO2 electrodes in water-containing electrolyte activates MnO2 electrode, after which improved Mg2+ capacity is maintained in dry Mg electrolyte. Based on a series of XPS analysis, a conversion mechanism is proposed where magnesiated MnO2 undergoes a conversion reaction to Mg(OH)2 and MnOx and Mn(OH)y species in the presence of water molecules. This conversion process is believed to be the driving force that generates the improved Mg2+ capacity in MnO2 along with the water molecule’s charge screening effect. Finally, it is discussed that upon a consecutive cycling of MnO2 in the water-containing Mg electrolyte, structural water is generated within the MnO2 lattice, which is thought to be the origin of the observed activation phenomenon. The results provided in this dissertation highlight that the divalency of Mg2+ ions result in very different electrochemical behaviors than those of the well-studied monovalent Li+ ions towards MnO2.

Nano-Engineering of Densely Packed Electrochemical Energy Storage Architectures by Atomic Layer Deposition

Nanostructures are highly attractive for future electrical energy storage devices because they enable large surface area and short ion transport time through thin electrode layers for high power devices. Significant enhancement in power density of batteries has been achieved by nano-engineered structures, particularly anode and cathode nanostructures spatially separated far apart by a porous membrane and/or a defined electrolyte region. A self-aligned nanostructured battery fully confined within a single nanopore presents a powerful platform to determine the rate performance and cyclability limits of nanostructured storage devices. Atomic layer deposition (ALD) has enabled us to create and evaluate such structures, comprised of nanotubular electrodes and electrolyte confined within anodic aluminum oxide (AAO) nanopores. The V2O5- V2O5 symmetric nanopore battery displays exceptional power-energy performance and cyclability when tested as a massively parallel device (~2billion/cm2), each with ~1m3 volume (~1fL). Cycled between 0.2V and 1.8V, this full cell has capacity retention of 95% at 5C rate and 46% at 150C, with more than 1000 charge/discharge cycles. These results demonstrate the promise of ultrasmall, self-aligned/regular, densely packed nanobattery structures as a testbed to study ionics and electrodics at the nanoscale with various geometrical modifications and as a building block for high performance energy storage systems[1, 2]. Further increase of full cell output potential is also demonstrated in asymmetric full cell configurations with various low voltage anode materials. The asymmetric full cell nanopore batteries, comprised of V2O5 as cathode and prelithiated SnO2 or anatase phase TiO2 as anode, with integrated nanotubular metal current collectors underneath each nanotubular storage electrode, also enabled by ALD. By controlling the amount of lithium ion prelithiated into SnO2 anode, we can tune full cell output voltage in the range of 0.3V and 3V. This asymmetric nanopore battery array displays exceptional rate performance and cyclability. When cycled between 1V and 3V, it has capacity retention of approximately 73% at 200C rate compared to 1C, with only 2% capacity loss after more than 500 charge/discharge cycles. With increased full cell output potential, the asymmetric V2O5-SnO2 nanopore battery shows significantly improved energy and power density. This configuration presents a more realistic test - through its asymmetric (vs symmetric) configuration – of performance and cyclability in nanoconfined environment. This dissertation covers (1) Ultra small electrochemical storage platform design and fabrication, (2) Electron and ion transport in nanostructured electrodes inside a half cell configuration, (3) Ion transport between anode and cathode in confined nanochannels in symmetric full cells, (4) Scale up energy and power density with geometry optimization and low voltage anode materials in asymmetric full cell configurations. As a supplement, selective growth of ALD to improve graphene conductance will also be discussed[3]. References: 1. Liu, C., et al., (Invited) A Rational Design for Batteries at Nanoscale by Atomic Layer Deposition. ECS Transactions, 2015. 69(7): p. 23-30. 2. Liu, C.Y., et al., An all-in-one nanopore battery array. Nature Nanotechnology, 2014. 9(12): p. 1031-1039. 3. Liu, C., et al., Improving Graphene Conductivity through Selective Atomic Layer Deposition. ECS Transactions, 2015. 69(7): p. 133-138.

Understanding Urban Stormwater Denitrification in Bioretention Internal Water Storage Zones

Free-draining bioretention systems commonly demonstrate poor nitrate removal. In this study, column tests verified the necessity of a permanently saturated zone to target nitrate removal via denitrification. Experiments determined a first-order denitrification rate constant of 0.0011 min-1 specific to Willow Oak woodchip media. A 2.6-day retention time reduced 3.0 mgN/L to below 0.05 mg-N/L. During simulated storm events, hydraulic retention time may be used as a predictive measurement of nitrate fate and removal. A minimum 4.0 hour retention time was necessary for in-storm denitrification defined by a minimum 20% nitrate removal. Additional environmental parameters, e.g., pH, temperature, oxidation-reduction potential, and dissolved oxygen, affect denitrification rate and response, but macroscale measurements may not be an accurate depiction of denitrifying biofilm conditions. A simple model was developed to predict annual bioretention nitrate performance. Novel bioretention design should incorporate bowl storage and large subsurface denitrifying zones to maximize treatment volume and contact time.