Today, hybrid electric propulsion technology provides a promising and practical solution for improving vehicle performance, increasing energy efficiency, and reducing harmful emissions, due to the additional flexibility that the technology has provided in the optimal power control and energy management, which are the keys to its success. In this work, a systematic approach for real-time optimal energy management of hybrid electric vehicles (HEVs) and plug-in hybrid electric vehicles (PHEVs) has been introduced and validated through two HEV/PHEV case studies. Firstly, a new analytical model of the optimal control problem for the Toyota Prius HEV with both offline and real-time solutions was presented and validated through Hardware-in-Loop (HIL) real-time simulation. Secondly, the new online or real-time optimal control algorithm was extended to a multi-regime PHEV by modifying the optimal control objective function and introducing a real-time implementable control algorithm with an adaptive coefficient tuning strategy. A number of practical issues in vehicle control, including drivability, controller integration, etc. are also investigated. The new algorithm was also validated on various driving cycles using both Model-in-Loop (MIL) and HIL environment. This research better utilizes the energy efficiency and emissions reduction potentials of hybrid electric powertrain systems, and forms the foundation for development of the next generation HEVs and PHEVs. / Graduate / laindeece@gmail.com

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.

This thesis deals withmodeling and control of an electric drive equipped with a permanentmagnet assisted synchronous reluctance (PMSynRel) machine for a plug-in hybrid electric vehicle application. In the first part of the thesis, a special use of the PMSynRel machine in consideration, known as an integrated charger concept, is investigated. The integrated charger feature allows using the PMSynRel machine as a part of the vehicle’s on-board charging system when charging the battery from the grid. A finite-element based analysis is performed providing important insights into the machine operation during the charging process. Dynamic models are developed that facilitate the controller development and the estimation of the efficiency during charging. In the second part of the thesis, position sensorless control of the PMSynRel drive when applied in an automotive application is considered and analyzed thoroughly. First, a fundamental-excitation based rotor-position estimation technique is investigated. The study shows that the impact of current dynamics on the resulting torque dynamics has to be considered in some very demanding applications. Second, focus is put on signalinjection based sensorless control methods. Impacts of nonlinearities, such as magnetic saturation, cross-saturation and inductance spatial harmonics, on sensorless control performance are investigated and methods to improve the sensorless control quality are summarized and presented. An approach to determine the feasible region for operating sensorless at low-speeds without directly measuring the differential inductances is proposed. For the PMSynRel drive in consideration, the achievable maximum torque is limited when operating sensorless following the maximum-torque-per-ampere (MTPA) current reference trajectory at low-speeds. An optimization approach is therefore proposed which extends the output torque when operating sensorless while still maintaining a relatively high efficiency. To initialize the sensorless control correctly from standstill, the impact of the saturated magnetic bridges in the rotor is also investigated. Finally, torsional drive-train oscillations and active damping schemes are considered. An off-vehicle setup for implementing and evaluating different active damping schemes is proposed. Of particular interest for sensorless operation in automotive applications, the impact of slow speed estimation on the possibility to achieve good active damping control is investigated and a design approach that allows the implementation of an active damping scheme using estimated speed is suggested. / <p>QC 20140114</p>

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.

This master‘s thesis pertains to the design of a cargo truck with battery electric drivetrain. The presented design offers a solution which respects the technical requirements of such a vehicle, ergonomic needs of its crew, and demands on the aesthetics of a modern commercial vehicle. In consideration of the chosen drivetrain, this solution is proposed as a concept with an outlook of 10 to 15 years in the future. In keeping with the specified goals, this vehicle offers a novel appearance which attempts to characterize the electric drivetrain with certain visual elements, includes solutions that are readily available or currently in development, and optimizes ergonomics for maximum user comfort and safety.

The Well-To-Wheels (WTW) methodology is widely used for policy making in the transportation sector. In this paper updated WTW calculations are provided, relying on 2013 statistic data, for the carbon intensity (CI) of the European electricity mix; detail is provided for electricity consumed in each EU Member State (MS). An interesting aspect presented is the calculation of the GHG content of electricity traded between Countries, affecting the carbon intensity of the electricity consumed at national level. The amount and CI of imported electricity is a key aspect: a Country importing electricity from another Country with a lower CI of electricity will lower, after the trade, its electricity CI, while importing electricity from a Country with a higher CI will raise the CI of the importing Country. In average, the CI of electricity used in EU at low voltage in 2013 was 447 gCO2eq/kWh, which is the 17% less compared to 2009. Then, some examples of calculation of GHG emissions from the use of electric vehicles (EVs) compared to internal combustion engine vehicles are provided. The use of EVs instead of gasoline vehicles can save (about 60% of) GHG in all or in most of the EU MSs, depending on the estimated consumption of EVs. Compared with diesel, EVs show average GHG savings of around 50% and not savings at all in some EU MS.

This thesis explores the possibility of using an optimal control scheme called Model Predictive Control (MPC), to control climatization systems for electric vehicles. Some components of electric vehicles, for example the batteries and power electronics, are sensitive to temperature and for this reason it is important that their temperature is well regulated. Furthermore, like all vehicles, the cab also needs to be heated and cooled. One of the weaknesses of electric vehicles is their range, for this reason it is important that the temperature control is energy efficient. Once the range of electric vehicles is increased the down sides compared to traditional combustion engine vehicles decrease, which could lead to an increase in the usage of electric vehicles. This could in turn lead to a decrease of greenhouse gas emission in the transportation sector. With the help of MPC it is possible for the controller to take more factors into consideration when controlling the system than just temperature and in this thesis the power consumption and noise are also taken into consideration. A simple model where parts of the climate system’s circuits were seen as point masses was developed, with nonlinear heat transfers occurring between them, which in turn were controlled by actuators such as fans, pumps and valves. The model was created using Simulink and MATLAB, and the MPC toolbox was used to develop nonlinear MPC controllers to control the climate system. A standard nonlinear MPC, a nonlinear MPC with custom cost functions and a PI controller where all developed and compared in simulations of a cooling scenario. The controllers were designed to control the temperatures of the battery, power electronics and the cab of an electric vehicle. The results of the thesis indicate that MPC could reduce power consumption for the climate control system, it was however not possible to draw any final conclusions as the PI controller that the MPC controllers were compared to was not well optimized for the system. The MPC controllers could benefit from further work, most importantly by applying a more sophisticated tuning method to the controller weights. What was certain was that it is possible to apply this type of centralized controller to very complex systems and achieve robustness without external logic. Even with the controller keeping track of six different temperatures and controlling 15 actuators, the control loop runs much faster than real time on a modern computer which shows promise with regard to implementing it on an embedded system.

Recently in more or all electric vehicles, higher voltage batteries are used which employ large number of cells in series. Series connection among cells may lead to single point of failures, safety and charge equalization issues that demand complex control and costly and/or lossy battery management methods. Most present day high voltage batteries use dissipative-charge balancing methods, which result in poor efficiency, additional thermal management burden and lower overall vehicle range. Furthermore, the output voltages of such batteries remain unregulated and may widely change with load and environmental conditions, complicating the overall power pass design of the electrical power system. As a step forward to address these issues, this thesis studies a fault-tolerant regulated active high voltage electric accumulator with integrated power electronics for safe charge and discharge of the high voltage energy storage system. / Thesis / Master of Applied Science (MASc)

No description available.

The automotive industry is facing some of the most difficult design challenges in industry history. Developing innovative methods to reduce fossil fuel dependence is imperative for maintaining compliance with government regulations and consumer demand. In addition to powertrain design, route selection contributes to vehicle environmental impact. The objective of this thesis is to develop a methodology for evaluating the energy consumption of each route option for a specific vehicle. A 'backwards' energy tracking method determines tractive demand at the wheels from route requirements and vehicle characteristics. Next, this method tracks energy quantities at each powertrain component. Each component model is scalable such that different vehicle powertrains may be approximated. Using an 'ecorouting' process, the most ideal route is selected by weighting relative total energy consumption and travel time. Only limited powertrain characteristics are publicly available. As the future goal of this project is to apply the model to many vehicle powertrain types, the powertrain model must be reasonably accurate with minimal vehicle powertrain characteristics. Future work expands this model to constantly re-evaluate energy consumption with real-time traffic and terrain information. While ecorouting has been applied to conventional vehicles in many publications, electrified vehicles are less studied. Hybrid vehicles are particularly complicated to model due to additional components, systems, and operation modes. This methodology has been validated to represent conventional, battery electric, and parallel hybrid electric vehicles. A sensitivity study demonstrates that the model is capable of differentiating powertrains with different parameters and routes with different characteristics. / Master of Science