Hybrid electric vehicles (HEVs) were introduced in response to rising environmental challenges facing the automotive sector. HEVs combine the benefits of electric vehicles and conventional internal combustion engine vehicles, integrating an electrical system (a battery and an electric motor) with an engine to provide improved fuel economy and reduced emissions, while maintaining adequate driving range. By comparison with conventional HEVs, plug-in hybrid electric vehicles (PHEVs) have larger battery storage systems and can be fully charged via an external electric power source such as the electrical grid. Of the three primary PHEV architectures, power-split architectures tend to provide greater efficiencies than parallel or series systems; however, they also demonstrate more complicated dynamics. Thus, in this research project, the problem of optimizing the component sizes of a power-split PHEV was addressed in an effort to exploit the flexibility of this powertrain system and further improve the vehicle's fuel economy, using a Toyota plug-in Prius as the baseline vehicle. Autonomie software was used to develop a vehicle model, which was then applied to formulate an optimization problem for which the main objective is to minimize fuel consumption over standard driving cycles. The design variables considered were: the engine's maximum power, the number of battery cells and the electric motor's maximum power. The genetic algorithm approach was employed to solve the optimization problem for various drive cycles and an acceptable reduction in fuel consumption was achieved thorough the sizing process. The model was validated against a MapleSim model. This research project successfully delivered a framework that integrates an Autonomie PHEV model and genetic algorithm optimization and can be used to address any HEV parameter optimization problem, with any objective, constraints, design variables and optimization parameters.

The automotive industry has long been searching for efficient ways to improve vehicle performance such as drivability, fuel consumption, and emissions. Researchers in the automotive industry have tried to develop methods to improve fuel consumption and reduce the emission gases of a vehicle, while satisfying drivability and ride comfort issues. Today, by developing computer/software technologies, automotive manufacturers are moving more and more towards modelling a real component (prototype) in a software domain (virtual prototype). For instance, modelling the components of a vehicle's powertrain (driveline) in the software domain helps the designers to iterate the model for different operating conditions and scenarios to obtain better performance without any cost of making a real prototype. The objective of this research is to develop and validate physics-based powertrain models with sufficient fidelity to be useful to the automotive industry for rapid prototyping. Developing a physics-based powertrain model that can accurately simulate real phenomenon in the powertrain components is of great importance. For instance, a high-fidelity simulation of the combustion phenomenon in the internal combustion (IC) engine with detailed physical and chemical reactions can be used as a virtual prototype to estimate physical prototype characteristics in a shorter time than it would take to build a physical prototype. Therefore, the powertrain design can be explored and validated virtually in the software domain to reduce the cost and time of product development. The main focus of this thesis is on development of an internal combustion engine model, four-cylinder spark ignition engine, and a hydrodynamic torque converter model. Then, the models are integrated along with the rest of a powertrain's components (e.g. vehicle longitudinal dynamics model) through acausal connections, which represents a more feasible physics-based powertrain model for model-based control design. The powertrain model can be operated at almost all operating conditions (e.g. wide range of the engine speeds and loads), and is able to capture some transient behaviour of the powertrain as well as the steady state response. Moreover, the parametric formulation of each component in the proposed powertrain model makes the model more efficient to simulate different types of powertrain (e.g. for a passenger car or truck).

Stricter regulations and evolving environmental concerns have been exerting ever-increasing pressure on the automotive industry to produce low carbon vehicles that reduce emissions. As a result, increasing numbers of alternative powertrain architectures have been released into the marketplace to address this need. However, with a myriad of possible alternative powertrain configurations, which is the most appropriate type for a given vehicle class and duty cycle? To that end, comparative analyses of powertrain configurations have been widely carried out in literature; though such analyses only considered limited types of powertrain architectures at a time. Collating the results from these literature often produced findings that were discontinuous, which made it difficult for drawing conclusions when comparing multiple types of powertrains. The aim of this research is to propose a novel methodology that can be used by practitioners to improve the methods for comparative analyses of different types of powertrain architectures. Contrary to what has been done so far, the proposed methodology combines an optimisation algorithm with a Modular Powertrain Structure that facilitates the simultaneous approach to optimising multiple types of powertrain architectures. The contribution to science is two-folds; presenting a methodology to simultaneously select a powertrain architecture and optimise its component sizes for a given cost function, and demonstrating the use of multi-objective optimisation for identifying trade-offs between cost functions by powertrain architecture selection. Based on the results, the sizing of the powertrain components were influenced by the power and energy requirements of the drivecycle, whereas the powertrain architecture selection was mainly driven by the autonomy range requirements, vehicle mass constraints, CO2 emissions, and powertrain costs. For multi-objective optimisation, the creation of a 3-dimentional Pareto front showed multiple solution points for the different powertrain architectures, which was inherent from the ability of the methodology to concurrently evaluate those architectures. A diverging trend was observed on this front with the increase in the autonomy range, driven primarily by variation in powertrain cost per kilometre. Additionally, there appeared to be a trade-off in terms of electric powertrain sizing between CO2 emissions and lowest mass. This was more evident at lower autonomy ranges, where the battery efficiency was a deciding factor for CO2 emissions. The results have demonstrated the contribution of the proposed methodology in the area of multi-objective powertrain architecture optimisation, thus addressing the aims of this research.

Traction inverter, as a critical component in electrified transportation, has been the subject of many research studies in terms of topologies, modulation, and control schemes. Recently, some of the well-known electric vehicle manufacturers have utilized higher-voltage batteries to benefit from lower current, higher power density, and faster charging times. With the ongoing trend toward higher voltage DC-link in electric vehicles, some multilevel structures have been investigated as a feasible and efficient option for replacing the two-level inverters. Higher efficiency, higher power density, better waveform quality, and inherent fault-tolerance are the foremost advantages of multilevel inverters which make them an attractive solution for this application. The first contribution of this thesis is to investigate and present a comprehensive review of the multilevel structures in traction applications. Secondly, this thesis proposes an electro-thermal model based on foster equivalent thermal networks for a designed three-level active neutral point clamped (ANPC) inverter, as well as a modified sinusoidal pulse-width modulation (SPWM) -based technique. This electro-thermal model and the modulation technique enable temperature estimation in the inverter and minimization of the hotspot temperature and hence, increase the power density. Based on the experimental results derived from the implemented setup, a 12% increase in power density is achieved with the proposed technique. The other contribution is a reduced-complexity model-predictive controller (MPC) for the three-level ANPC inverter without weighting factors in which the number of calculations has dropped from 27 to 12 in each sampling period. The improvements to the structure and control system of the inverter are supported by theoretical analysis, simulation results, and experimental tests. A three-level inverter is implemented for 800 V, 70 kW operation and tested. 750 V Silicon Carbide (SiC) switches are utilized in the inverter structure. Finally, future trends and suggestions for the following studies are stated in this thesis. / Thesis / Doctor of Philosophy (PhD)

The incorporation of detailed chemistry models in internal combustion engine simulations is becoming mandatory as new combustion strategies and lower global emissions limits are setting the path towards a more efficient engine cycle simulation tool. In this report, the computational capability of the stochastic-based Kinetics SRM engine suite by CMCL Innovations is evaluated in depth. With the main objectives of this research to create a multi-physics co-simulation framework and improve the traditional engine modelling approach of individual simulation of engine system parts, the Kinetics SRM code was coupled with a GT-SUITE engine model to fill in the gap of accurate emissions predictions from one-dimensional simulation tools. The system was validated against testing points collected from the AJ133 V8 5L GDI engine running on the NEDC. The Kinetics SRM model is further advanced through a sensitivity analysis for the “unknown” internal parameters of the chemistry tool. A set of new parameters’ values has been established that gives the best overall trade-off between prediction accuracy and computational time. However, it still showed high percentage errors in modelling the emissions and it was discovered that the specific software package currently cannot simulate directed injection events. This is the first time a Kinetics SRM/GT-SUITE coupled code is employed to model a full 8-cylinder GDI SI engine. The approach showed some limitations regarding the Kinetics SRM and that in many cases is limited to trend analysis. The coupled engine – combustion emissions model is then linked with an exhaust aftertreatment system model in MATLAB Simulink, creating a multi-physics model-based co-simulation framework of engine performance, combustion characterisation, in-cylinder emissions formation and aftertreatment efficiency.

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This thesis outlines the design and implementation process of an electrified powertrain for use in an American muscle car. Designed as McMaster University's entrant to the EcoCAR 3 Advanced Vehicle Technology Competition (AVTC), an electrified powertrain was developed to provide a Chevrolet Camaro with the performance expected by the American muscle car market while maintaining ever increasing fuel economy regulations. A background of current trends in vehicle electrification, including the prominent market segments experiencing these trends, will be explored along with the history of the classic and modern American muscle car's technical specifications. Following an investigation into existing vehicle electrification trends, the selected hybrid architecture will be discussed. The process of converting a conventional combustion powertrain into a series-parallel hybrid electric powertrain will be explored from the component-level through to full system design. Following a review of the design process for the powertrain, a high-level testing plan will be proposed using a number of test cells available within the facility. This plan will begin at the component-level exploring specific areas of potential complication and move up to complete system-level testing of powertrain functionality. / Thesis / Master of Applied Science (MASc) / Until recently, hybrid electric vehicles have tended to be available in a fairly limited market segment with few offerings for performance-oriented vehicle customers. The introduction of high performance hybrid vehicles suggests that this trend is likely to change. Increasingly more stringent fuel economy and emissions standards means that performance vehicle segments such as American muscle cars must adopt new technologies to retain their performance characteristics. Hybrid powertrains are one solution to providing and improving on the iconic performance of American muscle while meeting future regulatory changes. The addition of a number of electrified components to a gasoline powertrain can assist in achieving desired performance while reducing fuel economy. This thesis investigates the detailed design process adopted to make these modifications while maintaining the functionality expected by muscle car owners. After the design and assembly of the hybrid muscle car powertrain, a specific testing plan was laid out to ensure that the system is capable of sustaining the expected power output. This design and testing process can help introduce new hybrid vehicles to the market which are capable of meeting both the upcoming fuel economy regulations as well as the ongoing performance expectations of the muscle car market.

Personal vehicles have made great contributions to our life and satisfy our daily mobility needs. However, they have also caused societal issues, such as air pollution and global warming. Further to the recent attention to low-carbon energy technologies and environmentally friendly mobility, hybrid electric vehicles play an important role in the current automotive industry. As a leading center and an educational institution in Canada, McMaster University wants to build a Hybrid Electric Vehicle Powertrain Laboratory for introducing undergraduate students to hybrid powertrain architectures, instrumentation and control. A phased development of the hybrid powertrain teaching laboratory is being pursued. The first phase is to design a electric motor laboratory, as a platform for demonstrating motor characteristics. A LabVIEW based interface is designed to enable electric motor characterization tests. This laboratory set-up is still under construction. Real experiments would be implemented, once finishing the utility connections. For the hybrid powertrain laboratory, an innovative design architecture is proposed to enable different hybrid architectures, such as series, parallel, and power-split modes to be investigated. Instead of a planetary gearbox, bevel gearboxes with a continuous variable transmission (CVT) are used for making the laboratory more compact and flexible for demonstrating hybrid functionalities. The additional generator provides the ability of input power-split for allowing the engine to operate at a narrow high efficiency region. After designing the hybrid laboratory, a novel rule-based energy management strategy is applied to a simplified simulation model. / Thesis / Master of Applied Science (MASc)

The electric vehicle (EV) market is experiencing growth at an exponential rate, forcing automotive manufactures to invest in powertrain electrification. Manufactures are seeking low cost alternatives for electric propulsion motor technologies with switched reluctance motors (SRMs) having tremendous potential. The performance characteristics of SRMs designed for EV propulsion applications have yet to be experimentally verified. In this thesis, the operation of a 24/16 propulsion SRM specifically designed for a hybrid electric vehicle will be verified with a theoretical model and experimentally. The results are analyzed to gain further understanding of the factors affecting propulsion SRM operation. Two distinct theoretical models of a SRM are presented where one includes the effects of mutual coupling between two excited phases. The theoretical models and the experimental results indicate that for high power density SRMs, designed for propulsion applications, the effects of mutual coupling cannot be ignored. The motor is experimentally tested using a dynamometer machine. A test plan is presented which tests the motor at a wide speed and torque range suitable for EV applications. The testing procedure attempts to segregate the motor losses similar to international standards for induction machines and permanent magnet machines; however, these methods prove invalid due to the non-sinusoidal current in SRMs. Torque ripple minimization is highlighted to reduce the risk of detrimental speed fluctuation during motor testing with careful attention to thermal limitations. The SRM is tested using PWM current control as the baseline control method because hysteresis control is proven to be challenging for the tested SRM. The work presents many challenges associated with the testing and characterization of SRMs for propulsion applications; however, new research findings illustrate the potential of future improvements in propulsion SRM design and operation. / Thesis / Master of Applied Science (MASc)

As electric vehicles (EVs) are seen as the future of transportation, there are two significant challenges to overcome: range and cost. One effective strategy to address these issues is the optimization of powertrain components, which significantly impact both vehicle range and overall cost. In powertrain optimization, particular focus is placed on optimizing the electric motor and gearbox due to their crucial roles in vehicle performance and EV efficiency. A two-speed gearbox configuration for EVs has emerged as a solution to enhance dynamic performance and extend range. However, this approach comes with drawbacks such as increased weight and cost, leading to the prevalent use of single-speed gearboxes in the EV industry. Nonetheless, there is potential for optimizing motor size through the integration of a two-speed gearbox. The key question is whether the benefits of a smaller motor and increased vehicle range, enabled by a two-speed gearbox, outweigh its drawbacks. This study proposes a systematic method for co-optimizing the electric motor's sizing specifications and the gear ratios of a two-speed gearbox. This method achieved a 13% reduction in the required motor power for a sub-compact vehicle's specified 0-100 km/h acceleration, along with a significant motor weight reduction of up to 25%. Additionally, energy consumption was reduced by up to 3.8% for the EPA drive cycle while maintaining the same acceleration performance. / Thesis / Master of Applied Science (MASc)