No description available.

The powertrain design and control strategies for three representative hybrid and plug-in hybrid electric vehicles (HEV/PHEVs), a plug-in hybrid passenger car, a plug-in hybrid race car, and a hybrid electric mining truck, have been investigated through the system modeling, simulation and design optimization. First, the pre-transmission gen-set couple Plug-in Series-Parallel Multi-Regime (SPMR) powertrain architecture was selected for PHEV passenger car. Rule-based load following control schemes based on engine optimal control strategy and Equivalent Consumption Minimization Strategy (ECMS) were used for the operation control of the passenger car PHEV powertrain. Secondly, the rear wheel drive (RWD) post-transmission parallel through road powertrain architecture was selected for race car PHEV. A high level supervisory control system and ECMS control strategy have been developed and implemented through the race car’s on-board embedded controller using dSPACE MicroAutobox II. In addition, longitudinal adaptive traction control has been added to the vehicle controller for improved drivability and acceleration performance. At last, the feasibility and benefits of powertrain hybridization for heavy-duty mining truck have been investigated, and three hybrid powertrain architectures, series, parallel and diesel-electric, with weight adjusting propulsion system have been modeled and studied. The research explored the common and distinct characteristics of hybrid electric propulsion system technology for different vehicular applications, and formed the foundation for further research and development. / Graduate / 0540 / ruicheng@uvic.ca

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.

Georgia Tech has the privilege of competing in EcoCAR 3, a four-year competition in which 16 universities are given a stock 2016 Chevrolet Camaro and work to transform it into a hybrid electric sports car. In this thesis, an overview of the first two years of the author’s work on the team as the Engineering Manager, the graduate student overseeing all vehicle engineering work, will be detailed. The competition will be introduced and described before a discussion on vehicle electrification and the various ways it has been achieved by manufacturers and competition teams. Next, the design of the Georgia Tech vehicle will be presented with a focus on powertrain and supporting component selection. The vehicle model underlying many of these decisions will then be discussed in detail, showing how the team used Simulink and Engineering Equation Solver to effectively predict vehicle performance, emissions, energy consumption, and cooling needs. Building on this, the controls design process known as model/software/hardware in the loop will be discussed in the context of the Georgia Tech team’s use of this process. Finally, a progress update will be given, including photos of the team vehicle in current build state weeks before the Year 2 Competition.

Heavy duty powertrains are complex systems with components from various domains, different response times during transient operations and different efficient operating ranges. To ensure efficient transient operation of a powertrain, e.g. with low fuel consumption or short transient duration, it is important to come up with proper control strategies. In this dissertation, optimal control theory is used to calculate and analyze efficient heavy duty powertrain controls during transient operations in different applications. This is enabled by first developing control ready models, usable for multi-phase optimal control problem formulations, and then using numerical optimal control methods to calculate the optimal transients. Optimal control analysis of a wheel loader operating in a repetitive loading cycle is the first studied application. Increasing fuel efficiency or reducing the operation time in such repetitive loading cycles sums up to large savings over longer periods of time. Load lifting and vehicle traction consume almost all of the power produced by a diesel engine during wheel loader operation. Physical models are developed for these subsystems where the dynamics are described by differential equations. The model parameters are tuned and fuel consumption estimation is validated against measured values from real wheel loader operation. The sensitivity of wheel loader trajectory with respect to constrains such as the angle at which the wheel loader reaches the unloading position is also analyzed. A time and fuel optimal trajectory map is calculated for various unloading positions. Moreover, the importance of simultaneous optimization of wheel loader trajectory and the component transients is shown via a side to side comparison between measured fuel consumption and trajectories versus optimal control results. In another application, optimal control is used to calculate efficient gear shift controls for a heavy duty Automatic Transmission system. A modeling and optimal control framework is developed for a nine speed automatic transmission. Solving optimal control problems using the developed model, time and jerk efficient transient for simultaneous disengagement of off-going and engagement of in-coming shift actuators are obtained and the results are analyzed. Optimal controls of a diesel-electric powertrain during a gear shift in an Automated Manual Transmission system are calculated and analyzed in another application of optimal control. The powertrain model is extended by including driveline backlash angle as an extra state in the system. This is enabled by implementation of smoothing techniques in order to describe backlash dynamics as a single continuous function during all gear shift phases. Optimal controls are also calculated for a diesel-electric powertrain corresponding to a hybrid bus during a tip-in maneuver. It is shown that for optimal control analysis of complex powertrain systems, minimizing only one property such as time pushes the system transients into extreme operating conditions far from what is achievable in real applications. Multi-objective optimal control problem formulations are suggested in order to obtain a compromise between various objectives when analyzing such complex powertrain systems.

The paper describes the design of a prototype vehicle used by Dana Holding Corporation as a mobile laboratory for the development of Spicer® PowerBoost® hydraulic-hybrid powertrain technology. A telehandler vehicle was selected due to its versatility. Starting from the high-level requirements, design choices from the powertrain layout to the control architecture are discussed. The hydraulic-hybrid powertrain system is described, and its performance is analyzed based on representative driving cycles.

No description available.

My project revolves around an idea of implementing a new propulsion technology as a key design element. Batteries have in many ways been a revolution for how we propulsion cars today. It’s one of the best, if not the best, alternative for future power sources in cars. The downside however, is the fact that it dies out after a given range, and as we have learned, a battery takes time to reload. Range anxiety is an issue and IBM is currently trying to solve just that. They will by 2030 launch a new type of battery that will more than double the energy density of some of the most cutting edge lithium ion batteries of today.   The IBM-solution for a new battery is called “Battery 500” and is an open system technology that uses common air as a reagent which upon recharge releases oxygen back to the environment.  The battery would pull in and use oxygen in a similar way to how an internal combustion engine draws in oxygen.

<p>För att ett fordon ska kunna bromsa, accelerera och svänga är friktion mellan däcken och vägen ett måste. Vid för mycket gaspådrag under en acceleration kan det hända att hjulen förlorar fäste och börjar spinna loss, något som leder till både försämrad kontroll över fordonet och att däcken slits ut i förtid. Traction controlsystemet förhindrar hjulen från att spinna loss och försöker maximera friktionen.</p><p>Målet med detta examensarbete är att utvärdera olika reglerprinciper samt att undersöka olika möjligheter för att reglera friktionen mellan däck och väg. Det är ett svårt reglerproblem, dels på grund av dess olinjäritet, dels på grund av det faktum att friktionen är en okänd parameter.</p><p>För att kunna undersöka olika reglermöjligheter har en modell över hjuldynamiken och en modell över drivlinan tagits fram i Matlabs simuleringsprogram Simulink. Därutöver har tre regulatorer designats: en fuzzy-regulator, en fuzzy-P-regulator och en PI-regulator. Regulatorerna utvärderades i tre tester som bland annat testade deras robusthet.</p><p>Fuzzy-regulatorn och fuzzy-P-regulatorn lyckades reglera systemet bra. PI-regulatorn gjorde däremot inte ett tillfredsställande jobb, mest på grund av dess behov av ett börvärde.</p> / <p>Traction is necessary for a vehicle to be able to brake, accelerate and turn. When pushing the accelerator pedal too hard during an acceleration, the wheel can loose traction and start spinning, which leads to a worsen vehicle control and also wears out the tyres faster. The traction control system prevents the wheels from spinning and tries to make the tyres maintain maximum traction.</p><p>The purpose of this master’s thesis is to evaluate different control methods and to investigate possible ways to control the traction. This is a difficult control problem due to its nonlinearity and the fact that the friction is an unknown parameter.</p><p>For the investigation, a model of the wheel dynamics and a model of the powertrain have been developed in Matlab’s simulation program Simulink. Furthermore, three different controllers have been designed; a fuzzy controller, a fuzzy-P controller and a PI controller. The controllers were evaluated in three test cycles that among others tested their robustness.</p><p>The fuzzy controller and the fuzzy-P controller managed to control the system very well. The PI controller, however, did not work satisfactory, mainly because of its need of a desired value.</p>

För att ett fordon ska kunna bromsa, accelerera och svänga är friktion mellan däcken och vägen ett måste. Vid för mycket gaspådrag under en acceleration kan det hända att hjulen förlorar fäste och börjar spinna loss, något som leder till både försämrad kontroll över fordonet och att däcken slits ut i förtid. Traction controlsystemet förhindrar hjulen från att spinna loss och försöker maximera friktionen. Målet med detta examensarbete är att utvärdera olika reglerprinciper samt att undersöka olika möjligheter för att reglera friktionen mellan däck och väg. Det är ett svårt reglerproblem, dels på grund av dess olinjäritet, dels på grund av det faktum att friktionen är en okänd parameter. För att kunna undersöka olika reglermöjligheter har en modell över hjuldynamiken och en modell över drivlinan tagits fram i Matlabs simuleringsprogram Simulink. Därutöver har tre regulatorer designats: en fuzzy-regulator, en fuzzy-P-regulator och en PI-regulator. Regulatorerna utvärderades i tre tester som bland annat testade deras robusthet. Fuzzy-regulatorn och fuzzy-P-regulatorn lyckades reglera systemet bra. PI-regulatorn gjorde däremot inte ett tillfredsställande jobb, mest på grund av dess behov av ett börvärde. / Traction is necessary for a vehicle to be able to brake, accelerate and turn. When pushing the accelerator pedal too hard during an acceleration, the wheel can loose traction and start spinning, which leads to a worsen vehicle control and also wears out the tyres faster. The traction control system prevents the wheels from spinning and tries to make the tyres maintain maximum traction. The purpose of this master’s thesis is to evaluate different control methods and to investigate possible ways to control the traction. This is a difficult control problem due to its nonlinearity and the fact that the friction is an unknown parameter. For the investigation, a model of the wheel dynamics and a model of the powertrain have been developed in Matlab’s simulation program Simulink. Furthermore, three different controllers have been designed; a fuzzy controller, a fuzzy-P controller and a PI controller. The controllers were evaluated in three test cycles that among others tested their robustness. The fuzzy controller and the fuzzy-P controller managed to control the system very well. The PI controller, however, did not work satisfactory, mainly because of its need of a desired value.