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A series hybrid electric vehicle is a vehicle that is powered by both an engine and a battery pack. An electric motor provides all of the mechanical motive power to the transmission. Engine power is decoupled from the transmission by converting engine power into electricity which powers the electric motor. The mechanical decoupling of the engine from the transmission allows the engine to be run at any operating point (including off) during vehicle operation while the battery back supplies or consumes the remaining power. Therefore, the engine can be operated at its most efficient operating point or in a high-efficiency operating region. The first objective of this research is to develop a dynamic model of a series hybrid diesel-electric powertrain for implementation in Simulink. The vehicle of interest is a John Deere M-Gator utility vehicle. This model serves primarily to test energy management strategies, but it can also be used for component sizing given known load profiles for a vehicle. The second objective of this research is to develop and implement multiple energy management strategies of varying complexity from simple thermostat control to an optimal control law derived using dynamic programming. These energy management strategies are then tested and compared over the criteria of overall fuel efficiency, power availability, battery life, and complexity of implementation. Complexity of implementation is a critical metric for control designers and project managers. The results show that simple point-based control logic can improve upon thermostat control if engine efficiency maps are known. All control method results depend on the load profile being used for a specific application.

The widely-used passenger and car ferries, sailing regularly and carrying heavy loads, form a unique type of marine vessel, providing vital transportation links to the coastal regions. Modern ferry ships usually are equipped with multiple diesel engines as prime movers. These diesel engines consume a large amount of marine diesel fuel with high fuel costs, and high emissions of greenhouse gas (GHG) and other harmful air pollutants, including CO2, HC, NOx, SO2, CO, and PM. To reduce fuel costs and the harmful emissions, the marine industry and ferry service providers have been seeking clean ship propulsion solutions. In this work, the model-based design (MBD) and optimization methodology for developing advanced electrified vehicles (EV) are applied to the modelling, design and control optimizations of clean marine vessels with a hybrid electric propulsion system. The research focuses on the design and optimization of the hybrid electric ship propulsion system and uses an open deck passenger and car ferry, the MV Tachek, operated by the British Columbia Ferry Services Inc. Canada, as a test case. At present, the ferry runs on the Quadra Island – Cortes Island route in British Columbia, Canada, with dynamically changing ocean conditions in different seasons over a year. The research first introduces the ship operation profile, using statistical ferry operation data collected from the ferry’s voyage data recorder and a data acquisition system that is specially designed and installed in this research. The ship operation profile model with ship power demand, travelling velocity and sailing route then serves as the design and control requirements of the hybrid electric marine propulsion system. The development of optimal power control and energy management strategies and the optimization of the powertrain architecture and key powertrain component sizes of the ship propulsion system are then carried out. Both of the series and parallel hybrid electric propulsion architectures have been studied. The sizes of crucial powertrain components, including the diesel engine and battery energy storage system (ESS), are optimized to achieve the best system energy efficiency. The optimal power control and energy management strategies are optimized using dynamic programming (DP) over a complete ferry sailing trip. The predicted energy efficiency and emission reduction improvements of the proposed new ship with the optimized hybrid propulsion system are compared with those of two benchmark vessels to demonstrate the benefits of the new design methodology and the optimized hybrid electric ship propulsion system design. These two benchmarks include a conventional ferry with the old diesel-mechanical propulsion system, and the Power Take In (PTI) hybrid electric propulsion systems installed on the MV Tachek at present. The simulation results using the integrated ship propulsion system model showed that the newly proposed hybrid electric ship could have 17.41% fuel saving over the conventional diesel-mechanical ship, and 22.98% fuel saving over the present MV Tachek. The proposed optimized hybrid electric propulsion system, combining the advantages of diesel-electric, pure electric, and mechanical propulsions, presented considerably improved energy efficiency and emissions reduction. The research forms the foundation for future hybrid electric ferry design and development. / Graduate

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In recent years many companies have investigated the use of hybrid technology due to the potential of increasing the driveline’s efficiency and thus reducing fuel consumption. Previous studies show that hydraulic hybrid technology can be favourable to use in construction machinery such as wheel loaders, which often operate in repetitive drive cycles and have high transient power demands. Parallel as well as Series hybrid configurations are both found suitable for wheel loader applications as the hybrid configurations can decrease the dependency on the torque converter. This project has investigated a novel hydraulic hybrid concept which utilizes the wheel loaders auxiliary pump as a supplement to enable both Series and Parallel hybrid operation. Impact of accumulator sizes has also been investigated, for which smaller accumulator sizes resembles a hydrostatic transmission. The hybrid concept has been evaluated by developing a wheel loader simulation model and a control system based on a rule-based energy management strategy. Simulation results indicate improved energy efficiency of up to 18.80 % for the Combined hybrid. Moreover, the accumulator sizes prove to have less impact on the energy efficiency. A hybrid system with decreased accumulator sizes shows improved energy efficiency of up to 16.40 %.

Unidades propulsoras híbrido elétricas são uma alternativa em potencial para a redução do consumo de combustível e emissões de poluentes, quando empregadas em veículos de transporte público. A configuração híbrido elétrica de interesse é a série, na qual as fontes de potência, para o motor elétrico de tração, são compostas por um banco de baterias e uma unidade formada pela junção entre um motor à combustão interna e um gerador. Na presente Dissertação foi realizada a modelagem de um veículo elétrico híbrido série na qual diferentes estratégias de gerenciamento de potência foram investigadas. Dentre as estratégias de interesse, duas são fundamentadas em regras e a terceira em sistemas fuzzy. Resultados obtidos comprovaram que a fundamentada em sistemas fuzzy possibilita maior economia de combustível, permitindo que o motor à combustão interna forneça menos potência, face o emprego das baseadas em regras. Dessa forma, a utilização de sistemas fuzzy no gerenciamento de potência do veículo, permite o emprego de um motor à combustão menos potente, de menor custo, sem o comprometimento do desempenho do veículo. As simulações do presente modelo de veículo híbrido foram realizadas no ambiente Matlab/Simulink® 7.3.0. / Hybrid electric propulsion units are a potential alternative to the reduction of fuel consumption and pollutant emissions, when used in public transport vehicles. The electric hybrid configuration of interest is the series, in which the energy supplies to the traction electric motor are composed of batteries and a unit represented by the connection of an internal combustion engine and a generator. This Dissertation presents the modeling of a series hybrid electric vehicle in which different energy management strategies were investigated. Among the strategies of interest, two are based on rules and one on fuzzy systems. The obtained results proved that the strategy based on fuzzy systems improved the fuel economy, allowing the internal combustion engine to supply less power than the use of the strategies based on rules. Therefore, the use of fuzzy systems in the energy management of the vehicle allows for the adoption of a less potent and cheaper internal combustion engine, without compromising the vehicles performance. The simulations of the present model of the hybrid electric vehicle were performed in the Matlab/Simulink® 7.3.0 environment.

In recent years, rules and regulations regarding fuel consumption of vehicles and the amount of emissions produced by them are becoming stricter. This has led the automotive industry to develop more advanced solutions to propel vehicles to meet the legal requirements. The Hybrid Electric Vehicle is one of the solutions that is becoming more popular in the automotive industry. It consists of an electrical driveline combined with a conventional powertrain, propelled by either a diesel or petrol engine. Two power sources create the possibility to choose when and how to use the power sources to propel the vehicle. The strategy that decides how this is done is referred to as an energy management strategy. Today most energy management strategies only try to reduce fuel consumption using models that describe the steady state behaviour of the engine. In other words, no reduction of emissions is achieved and all transient behaviour is considered negligible.  In this thesis, an energy management strategy incorporating engine dynamics to reduce fuel consumption and nitrogen oxide emissions have been designed. First, the models that describe how fuel consumption and nitrogen oxide emissions behave during transient engine operation are developed. Then, an energy management strategy is developed consisting of a model predictive controller that combines the equivalent consumption minimization strategy and convex optimization. Results indicate that by considering engine dynamics in the energy management strategy, both fuel consumption and nitrogen oxide emissions can be reduced. Furthermore, it is also shown that the major reduction in fuel consumption and nitrogen oxide emissions is achieved for short prediction horizons.