This thesis presents two simulations of a heavy hybrid vehicle, the first part of the thesis is focused on the specifications of the vehicle designed in accordance with the requirements based on the literature study of the soils where the vehicle will travel. The second part presents the study of the vehicle through two simulations. The first simulation is oriented on the dynamical behavior of the vehicle. The second simulation focuses on the energy management of the vehicle. The presented thesis is a multi-disciplinary study, combining knowledge on vehicle dynamics, hydraulic suspensions and hybrid systems. The dynamical simulation of the vehicle has been performed with Matlab/Simulink and the third party program Delft-Tire for the tire modelling. Specials features of Matlab have been used; SimMechanics for the modelling of the parts, links and joints of the vehicle, and SimHydraulics for the modelling of the hydraulic suspensions. The principal tests performed on the vehicle by the dynamical simulation are the tests defined by the NATO - STANAG standards as AVTP 03-170. The tests are a crossing obstacle test and different sine wave roads. The obstacle of the obstacle crossing test is an APG-10 obstacle, an 10 inch high step with vertical edges. The objective of this simulation is to verify the design of the suspension and to observe the forces created in each link of the suspension system in order to design the chassis and the suspension system. The sine wave driving tests are performed to highlight the influence of the different hydraulic connections. Finally the slalom test presents the influence of the hydraulic anti-roll bar. The results show that the vehicle suspension verifies the STANAG standard. The results show also that the forces applied at the wheel by the obstacle crossing defined in the AVTP 03- 170 are directly related to the diameter and the stiffness of the tire. The maximum forces encountered at the wheel corresponds to 2.5 G vertically and 1.5 G longitudinally. The sine wave driving and the slalom test are showing the benefits and the need for advanced hydraulic suspensions. The second simulation is the modelling of the hybrid power management of the vehicle. The simulation has been performed with the objectives to create a tool for sizing series hybrid powertrain. This simulation has also been performed with Matlab/Simulink and the Simscape Library. The tool created show that when, the vehicle is equipped with 150 kW of power generation and 300 kW of battery would be able to drive at a constant speed of 10 km/h with the terrain inputs evaluated from the literature study, but to create sufficient result the input parameters of the tools need to have a better definition.

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<p>This thesis presents the design stages in creating a robotic driving system for performing in-lab driving schedule playback using a chassis dynamometer. This equipment is intended to assist research in improving the power train system in Hybrid Electric Vehicles (HEV). The design stage layout contributes to showing how to effectively breakdown a mechatronics related project into manageable steps. The process includes background research, system requirements, system design and validation. Design stages are further broken up into three subsystems, mechanical, electrical and software.</p> <p>Two actuators control the gas and brake pedals of the test vehicle. An active control system allows the vehicle to follow a speed vs. time driving schedule. The control feedback loop uses two cascading Proportional-Integral (PI) controllers (vehicle speed and pedal position). Feedback signals come from the onboard diagnostics (OBD-II) port. The control software is implemented on a dSPACE MicroAutoBox capable of multiple inputs and outputs including a built in CAN Bus controller to receive messages from the OBD-II port. The control software is implemented in Simulink and provides a modular, maintainable architecture for future development.</p> <p>The system design steps lead to a practical system obtained through a systematic approach. Design documentation will allow for further development of this test system to meet future requirements.</p> / Master of Applied Science (MASc)

This thesis outlines the development of a control system for a series-parallel plugin hybrid electric vehicle. The vehicle, developed at McMaster University for the EcoCAR 3 Advanced Vehicle Technology Competition, was produced in an effort to provide a Chevrolet Camaro with a high-performance, fuel efficient, hybrid powertrain. A rational design methodology was adopted and guided the development of the control system and the implementation of its respective algorithms. A simulation tool was created using MATLAB and Simulink which, in turn, allowed for the effectiveness of the supervisory control logic to be evaluated by approximating the vehicle’s energy consumption, fuel consumption, and emissions. The impact of hybridizing the vehicle’s powertrain was similarly assessed by comparing it against its unelectrified counterpart, the 2016 Chevrolet Camaro LT. A solution to the vehicle’s energy management problem was proposed in the form of an Adaptive Equivalent Consumption Minimization Strategy (A-ECMS) which was then evaluated against more common heuristic approaches as well as non-adaptive instantaneous minimization methods. An artificial neural network was selected as the strategy’s adaptation mechanism and it was used to identify specific vehicular driving patterns in real-time. The neural network addresses many issues that arise due to the sensitivity of algorithms that attempt to solve the energy management problem without prior knowledge of the driving cycle. The methods used during the process of the control system’s verification and calibration are also discussed in this thesis and, in addition, encompass the use of software representations of the vehicle’s Electronic Control Units (ECUs), the development of test cases, and the supervisory control software’s evaluation in the Model-in-the-Loop (MIL), Software-in-the-Loop (SIL), and Hardware-in-the-Loop (HIL) environments. / Thesis / Master of Applied Science (MASc) / Compared to conventional combustion vehicles, an automobile with an electrified propulsion system has the potential to reduce fuel consumption and emissions due to the presence of an energy storage system and one or more electric machines. These benefits, however, come at the cost of increased control system complexity. The question of how and when to use alternative energy sources – whether it be electrical or fuel energy – in a hybrid vehicle is at the epicenter of research and development initiatives in the automotive industry. Traditional heuristic methods have proven to be unstable due to their sensitivity to driving conditions and that optimal control policies require prior knowledge of the vehicle’s route and destination, and therefore, are not suitable in most applications. Strategies which attempt to instantaneously minimize a vehicle’s fuel or energy consumption, however, can overcome these aforementioned obstacles. As such, this area of research and development has received much interest. The objective of this research was twofold: the first being to develop a control system for a series-parallel plug-in hybrid electric vehicle in a rational and systematic manner, and, secondarily, to evaluate the benefits of instantaneous minimization methods for energy management.