Following the Model-Based-Design (MBD) development process used presently by the automotive industry, the control systems for a new Series-Parallel Multiple-Regime Plug-in Hybrid Electric Vehicle (PHEV), UVic EcoCAR2, have been developed, implemented and tested. Concurrent simulation platforms were used to achieve different developmental goals, with a simplified system power loss model serving as the low-overhead control strategy optimization platform, and a high fidelity Software-in-Loop (SIL) model serving as the vehicle control development and testing platform. These two platforms were used to develop a strategy-independent controls development tool which will allow deployment of new strategies for the vehicle irrespective of energy management strategy particulars. A rule-based energy management strategy was applied and calibrated using genetic algorithm (GA) optimization. The concurrent modeling approach was validated by comparing the vehicle equivalent fuel consumption between the simplified and SIL models. An equivalency factor (EF) of 1 was used in accounting for battery state of charge (SOC) discrepancies at cycle end. A recursively-defined subsystem efficiency-based EF was also applied to try to capture real-world equivalency impacts. Aggregate results between the two test platforms showed translation of the optimization benefits though absolute results varied for some cycles. Accuracy improvements to the simplified model to better capture dynamic effects are recommended to improve the utility of the newly introduced vehicle control system development method. Additional future work in redefining operation modes and mode transition threshold conditions to approximate optimal vehicle operation is recommended and readily supported by the control system platform developed. / Graduate / 0540 / 0548 / 0790 / d.e.prescott@gmail.com

Increasing debates over a gasoline independent future and the reduction of greenhouse gas (GHG) emissions has led to a surge in plug-in hybrid electric vehicles (PHEVs) being developed around the world. Due to the limited all-electric range of PHEVs, a daytime PHEV charging infrastructure will be required for most PHEVs’ daily usage. This dissertation, for the first time, presents a mixed integer mathematical programming model to solve the PHEV charging infrastructure planning (PCIP) problem. Our case study, based on the Oak Ridge National Laboratory (ORNL) campus, produced encouraging results, indicates the viability of the modeling approach and substantiates the importance of considering both employee convenience and appropriate grid connections in the PCIP problem. Unfortunately, the classical optimization methods do not scale up well to larger practical problems. In order to effectively and efficiently attack larger PCIP problems, we develop a new MASTS based TS algorithm, PCIP-TS to solve the PCIP. The results from computational experiments for the ORNL campus problem establish the dominant supremacy of the PCIP-TS method both in terms of solution quality and computational time. Additional experiments with simulated data representative of a problem that might be faced by a small city show that PCIP-TS outperforms CPLEX based optimization. Once the charging infrastructure is in place, the immediate problem is to judiciously manage this system on a daily basis. This thesis formally develops a mixed integer linear program to solve the daily the energy management problem (DEM) faced by an organization and presented results of a case study performed for ORNL campus. The results from our case study, based on the Oak Ridge National Laboratory (ORNL) campus, are encouraging and substantiate the importance of controlled PHEV fleet charging and realizing V2G capabilities as opposed to uncontrolled charging methods. Although optimal solutions are obtained, the solver requires practically unacceptable computational times for larger problems. Hence, we develop a new MASTS based TS algorithm, DEM-TS, for the DEM models. Results for ORNL campus data set prove the dominant computational efficiency of the DEM-TS. For the simulated extended sized problems that resemble the complexity of a problem faced by a small city, the results prove that DEM-T not only achieves optimality, but also produces sets of multiple alternate optimal solutions. These could be very helpful in practical settings when alternate solutions are necessary because some solutions may not be deployable due to unforeseen circumstances. / text

Plug-in hybrid electric vehicles (PHEVs) represent a promising future direction for the personal transportation sector in terms of decreasing the reliance on fossil fuels while simultaneously decreasing emissions. Energy used for driving is fully or partially shifted to electricity leading to lower emission rates, especially in a low carbon intensive generation mixture such as that of British Columbia’s. Despite the benefits of PHEVs for vehicle owners, care will need to be taken when integrating PHEVs into existing electrical grids. For example, there is a natural coincidence between peak electricity demand and the hours during which the majority of vehicles are parked at a residence after a daily commute. This research aims to investigate the incremental impacts to distribution networks in British Columbia imposed by the charging of PHEVs. A probabilistic model based on Monte Carlo Simulations is used to investigate the impacts of uncontrolled PHEV charging on three phase networks in the BC electricity system. A model simulating daily electricity demand is used to estimate the residential and commercial demand on a network. A PHEV operator model simulates the actions of drivers throughout a typical day in order to estimate the demand for vehicle charging imposed on networks. A load flow algorithm is used to solve three phase networks for voltage, current and line losses. Representative three phase networks are investigated typical of suburban, urban and rural networks. Scenarios of increasing PHEV penetration on the network and technological advancement are considered in the absence of vehicle charging control. The results are analyzed in terms of three main categories of impacts: network demands, network voltage levels and secondary transformer overloading. In all of the networks, the PHEV charging adds a large amount of demand to the daily peak period. The increase in peak demand due to PHEV charging increases at a higher rate than the increase in energy supplied to the network as a result of vehicles charging at 240V outlets. No significant voltage drop or voltage unbalance problems occur on any of the networks investigated. Secondary transformer overloading rates are highest on the suburban network. PHEVs can also contribute to loss of transformer life specifically for transformers that are overloaded in the absence of PHEV charging. For the majority of feeders, uncontrolled PHEV charging should not pose significant problems in the near term. Recommendations are made for future studies and possible methods for mitigating the impacts.

The negative consequences of rising global energy use have led governments and businesses to pursue methods of reducing reliance on fossil fuels. Plug-In Hybrid Electric Vehicles (PHEVs) and wind power represent two practical methods for mitigating some of these negative consequences. PHEVs use large onboard batteries to displace gasoline with electricity obtained from the grid, while wind power generates clean, renewable power that has the potential to displace fossil-fuel power generation. The emissions reductions realized by these technologies will be highly dependent on the energy system into which they are integrated, and also how they are integrated. This research aims to assess to cost of reducing emissions through the integration of PHEVs and wind power in three Canadian jurisdictions, namely British Columbia, Ontario and Alberta. An Optimal Power Flow (OPF) model is used to assess the changes in generation dispatch resulting from the integration of wind power and PHEVs into the local electricity network. This network model captures the geographic distribution of load and generation in each jurisdiction, while simulating local transmission constraints. A linear optimization model is developed in the MATLAB environment and is solved using the ILOG CPLEX Optimization package. The model solves a 168-hour generation scheduling period for both summer and winter conditions. Simulation results provide the costs and emissions from power generation when various levels of PHEVs and/or wind power are added to the electricity system. The costs and emissions from PHEV purchase and gasoline displacement are then added to the OPF results and an overall GHG reduction cost is calculated. Results indicate that wind power is an expensive method of GHG abatement in British Columbia and Ontario. This is due to the limited environmental benefit of wind over the nuclear and hydro baseload mixtures. The large premium paid for displacing hydro or nuclear power with wind power does little to reduce emissions, and thus CO2e costs are high. PHEVs are a cheaper method of GHG abatement in British Columbia and Ontario, since the GHG reductions resulting from the substitution of gasoline for hydro or nuclear power are significant. In Alberta, wind power is the cheaper method of GHG abatement because wind power is closer in price to the coal and natural gas dominated Alberta mixture, while offering significant environmental benefits. PHEVs represent a more expensive method of GHG abatement in Alberta, since substituting gasoline for expensive, GHG-intense electricity in a vehicle does less to reduce overall emissions. Results also indicate that PHEV charging should take place during off-peak hours, to take advantage of surplus baseload generation. PHEV adoption helps wind power in Ontario and British Columbia, as overnight charging reduces the amount of cheap, clean baseload power displaced by wind during these hours. In Alberta, wind power helps PHEVs by cleaning up the generation mixture and providing more environmental benefit from the substitution of gasoline with electricity.

Two studies are presented quantifying the impact of plug-in hybrid vehicles (PHEVs) on power systems. The first study quantifies this impact in terms of (a) primary fuel utilization shifts, (b) pollution shifts, and (c) total cost for consumers. The second study quantifies this impact on distribution transformers. In the first study vehicle and power system simulations are used to compute the expected power system fuels utilized to meet a projected level of power demand. The projected electric power demand includes business as usual electric load and random PHEV charging electric load. In the second study the impact on distribution transformers is quantified through a loss of life calculation. The loss of life calculation is based on distribution transformer hot-spot temperature. The hot-spot temperature is estimated using an electro-thermal distribution transformer model and is a function of the transformer currents. The transformer currents are computed using a center-tapped single phase transformer model. Random business as usual and PHEV charging electric loading is assumed.

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Defining key parameters for a charge sustaining supervisory (torque split) control strategy as well as an engine and catalyst warm-up strategy for a Split Parallel Architecture Extended-Range Electric Vehicle (SPA E-REV) is accomplished through empirically and experimentally measuring vehicle tailpipe emissions and energy consumption for two distinct control strategies. The results of the experimental testing and analysis define how the vehicle reduces fuel consumption, petroleum energy use and greenhouse gas emissions while maintaining low tailpipe emissions. For a SPA E-REV operating in charge sustaining mode with the engine providing net propulsive energy, simply operating the engine in regions of highest efficiency does not equate to the most efficient operation of the vehicle as a system and can have adverse effects on tailpipe emissions. Engine and catalyst warm-up during the transition from all-electric charge depleting to engine-dominant charge sustaining modes is experimentally analyzed to evaluate tailpipe emissions. The results presented are meant to define key parameters for a high-level torque-split strategy and to provide an understanding of the tradeoffs between low energy consumption and low tailpipe emissions. The literature review gives a background of hybrid and plug-in hybrid vehicle control publications including tailpipe emissions studies, but does not include experimental results and comparisons of supervisory strategies designed for low fuel consumption and low tailpipe emissions the SPA E-REV architecture. This paper details the high-level control strategy chosen for balancing low energy consumption and low tailpipe emissions while the engine is operating. Vehicle testing data from a chassis dynamometer is presented in support of the research. / Master of Science

This work explores how GaN devices and advanced control can improve the power density of battery chargers for the plug-in hybrid electric vehicle. Gallium nitride (GaN) devices are used to increase switching frequency and shrink passive components. An innovative DC link reduction technique is proposed and several practical design issues are solved. A multi-chip-module (MCM) approach is used to integrate multiple GaN transistors into a package that enables fast, reliable, and efficient switching. The on-resistance and output charge are characterized. In a double pulse test, GaN devices show fast switching speed. The loss estimation based on the characterization results shows a good match with the measurement results of a 500 kHz GaN-based boost converter. Topology selection is conducted to identify candidates for the PHEV charger application. Popular topologies are reviewed, including non-isolated and isolated solutions, and single-stage and two-stage solutions. Since the isolated two-stage solution is more promising, the topologies consisting of an AC/DC front-end converter and an isolated DC/DC converters are reviewed. The identified candidate topologies are evaluated quantitatively. Finally, the topology of a full bridge AC/DC plus dual active bridge DC/DC is selected to build the battery charger prototype for fixed switching-frequency, low loss, and low realization complexity. The DC link capacitor is one of the major power density barriers of the charger, as its size cannot be reduced by increasing the switching frequency. This work proposed a charging scheme to reduce the DC link capacitance by balancing the ripple power from input and output given that the double-line-frequency current causes minor impact to the battery pack in terms of capacity and temperature rise. An in-depth analysis of ripple power balance, with converter loss considered, unveils the conditions of eliminating the low-frequency DC link capacitors. PWM-zero-off charging where the battery is charged by a current at double-line-frequency and DC/DC stage is turned off at the zero level of the waveform, is also proposed to achieve a better tradeoff between the DC link capacitor size and the charger efficiency. The practical design issues are outlined and the solutions are given at different levels of implementations, including the full bridge building block, the AC/DC stage, and the DC/DC stage. The full bridge section focuses on the solution of a reliable driving and sensing circuitry design. The AC/DC stage portion stresses the modulator improvement, which solves the often-reported issues of the current spike at the zero-crossing of the line voltage for the high frequency totem-pole bridgeless converter. In the DAB section, analytical expressions are given to model the converter operation at various operating conditions, which match well with the measurement results. The overall charging-system operation including the seamless transition of bi-directional power flow and the charging-profile control is verified on a laboratory GaN charger prototype at 500 kHz and 1.8 kW with an efficiency of 92.4%. To push the power density, some bulky components including the control board, the cooling system, and the chassis are redesigned. Together with other already-verified building blocks including full bridges, magnetics, and capacitors, a high-density mock-up prototype with 125 W/in3 power density is assembled. / Ph. D.