Hybrid Fuel Cell Vehicle Powertrain Development Considering Power Source Degradation

Vehicle design and control is an attractive area of research in that it embodies a convergence of societal need, technical limitation, and emerging capability. Environmental, political, and monetary concerns are driving the automotive industry towards sustainable transportation, manifested as increasing powertrain electrification in a gradual transition to fossil-free energy vectors. From an electrochemical degradation and control systems perspective, this transition introduces significant technical uncertainty. Initial indications are that the initial battery designs will have twice the required capacity due to degradation concerns. As the battery is a major contributor to the cost of these vehicles the over-sizing represents a significant threat to the ability of OEMs to produce cost-competitive vehicles. This potential barrier is further amplified when the combustion engine is removed and battery-electric or fuel-cell hybrid vehicles are considered. This thesis researches the application of model-based design for optimal design of fuel cell hybrid powertrains considering power source degradation. The intent is to develop and evaluate tools that can determine the optimal sizing and control of the powertrain; reducing the amount of over-sizing by numerically optimization rather than a sub-optimal heuristic design. A baseline hybrid fuel cell vehicle model is developed and validated to a hybrid fuel cell SUV designed and built at the University of Waterloo. Lithium-ion battery degradation models are developed and validated to data captured off a hybrid powertrain test stand built as part of this research. A fuel cell degradation model is developed and integrated into the vehicle model. Lifetime performance is modeled for four hybrid control strategies, demonstrating a significant impact of the hybrid control strategy on powertrain degradation. A plug-in variation of the architecture is developed. The capacity degradation of the battery is found to be more significant than the power degradation. Blended and All-electric charge-depleting hybrid control strategies are integrated and lifetime performance is simulated. The blended charge-depleting control strategy demonstrated significantly less degradation than the all-electric strategy. An oversized battery is integrated into the vehicle model and the benefit of oversizing on reducing the battery degradation rate is demonstrated

Extended Range Electric Vehicle Powertrain Simulation and Comparison with Consideration of Fuel Cell and Metal-air Battery

The automotive industry has been in a period of energy transformation from fossil fuels to a clean energy economy due to the economic pressures resulting from the energy crisis and the need for stricter environmental protection policies. Among various clean energy systems are electric vehicles, with lithium-ion batteries have the largest market share because of their stable performance and they are a relatively mature technology. However, two disadvantages limit the development of electric vehicles: charging time and energy density. In order to mitigate these challenges, vehicle Original Equipment Manufacturers (OEMs) have developed different vehicle architectures to extend the vehicle range, including the Hybrid Electric Vehicle (HEV), Plug-in Hybrid Electric Vehicle (PHEV), and Extended Range Electric Vehicle (EREV). In this project, two advanced EREV powertrains have been modeled and simulated by using a lithium-ion battery as the primary energy source, with the combination of a fuel cell (FCV) or zinc-air battery as the range extenders. These two technologies were chosen as potential range extenders because of their high energy density and low life cycle emissions. The objective of this project is to compare the combined energy system (zinc-air and lithium-ion battery, fuel cell and lithium-ion battery) powered vehicles with gasoline powered vehicles (baseline vehicle, ICE engine extended range electric vehicle) and battery electric vehicles (BEV) in dimensions of energy consumption, range, emissions, cost, and customer acceptance. In order to achieve this goal, a unique zinc-air battery model was developed in this work with consideration of research data and current market status, and a control logic of the dual energy systems powertrain was created in the vehicle modeling software. A 2015 Chevrolet Camaro had been chosen as the vehicle architecture platform, with modelling of the five vehicle powertrains being built within Autonomie. This vehicle modeling software, developed by Argonne National Laboratory, runs with MATLAB/Simulink, and contains embedded drive cycles and analysis tools needed to perform the necessary simulations. Since the emission analysis in the Autonomie model only considers the vehicle in energy consumption and tailpipe emissions, therefore a Well-to-Wheel analysis method is introduced to evaluate the energy life cycle. This method takes into account the emissions from the energy production and considers the vehicle tailpipe emission. After finished all the simulations, a decision matrix was developed to compare these five powertrains from the metrics of energy consumption, emissions, customer acceptance, and life cycle cost. Three substantial conclusions were obtained from the comparison: The powertrains without use engine and gasoline as the power source have the lower tailpipe emissions and greenhouse gas emissions. The powertrains based on battery power alone, i.e. metal air extended range electric vehicle (MA-EREV) and battery electric vehicle (BEV) are not able to achieve the total range target, likely because of the relative high vehicle mass caused by the weight of the battery pack. However MA-EREV got the highest marks compared to other powertrains. However, metal-air battery is a new technology, and there are no prototypes of the technology, thus full commercialization is expected to take some time

Torque Control Strategies for AWD Electric Vehicles

There is a fundamental shift occurring in the design of passenger vehicles for North American markets. While for decades automotive manufacturers have relied on internal combustion engines burning fossil fuels, the early 21st century has seen a departure from conventional thinking about powertrain design towards two new design paradigms: hybrid electric vehicles (HEVs), and fuel cell vehicles (FCVs). Hybrid electric vehicles incorporate a high power electric motor and an electrical storage system which are used for motive power in addition to their conventional internal combustion engine (ICE). Fuel cell vehicles use a stack of individual cells to produce electric power which is then used in an electric motor to move the vehicle. They are generally fueled by a stream of high purity hydrogen, and produce only water as an emission. Both vehicle types use electric motors as an integral component in their configuration. The objective for this thesis is to propose a control strategy for the traction motors of a hybrid or electric vehicle. In particular, it addresses the question of how to split torque between two onboard electric motors while considering the efficiency, stability, and traction of the vehicle. This work is based upon two hybrid vehicles: a Chevrolet Equinox converted to a Fuel Cell HEV, and a Chrysler Pacifica converted to an internal combustion engine HEV. A torque control strategy is recommended that focuses on improved efficiency while addressing vehicle stability, and traction control. The strategy also incorporates powertrain component protection. Simulations indicate that the manner in which torque is split between the motors can have a large impact on the total efficiency of the powertrain; greater than 7% improvement fuel economy is projected by using an intelligent torque control system over a iii FTP-75 drive cycle. It is recommended that this work be extended to incorporate regenerative braking and a more thorough analysis of vehicle stability and drivability

Advances in Electric Drive Vehicle Modeling with Subsequent Experimentation and Analysis

A combination of stricter emissions regulatory standards and rising oil prices is leading many automotive manufacturers to explore alternative energy vehicles. In an effort to achieve zero tail pipe emissions, many of these manufacturers are investigating electric drive vehicle technology. In an effort to provide University of Kansas students and researchers with a stand-alone tool for predicting electric vehicle performance, this work covers the development and validation of various models and techniques. Chapter 2 investigates the practicality of vehicle coast down testing as a suitable replacement to moving floor wind tunnel experimentation. The recent implementation of full-scale moving floor wind tunnels is forcing a re-estimation of previous coefficient of drag determinations. Moreover, these wind tunnels are relatively expensive to build and operate and may not capture concepts such as linear and quadratic velocity dependency along with the influence of tire pressure on rolling resistance. The testing method explained here improves the accuracy of the fundamental vehicle modeling equations while remaining relatively affordable. The third chapter outlines various models used to predict battery capacity. The authors investigate the effectiveness of Peukert's Law and its application in lithium-based batteries. The work then presents the various effects of battery temperature on capacity and outlines previous work in the field. This paper then expands upon Peukert's equation in order to include both variable current and temperature effects. The method proposed captures these requirements based on a relative maximum capacity criterion. Experimental methods presented in the paper provide an economical testing procedure capable of producing the required coefficients in order to build a high-level, yet accurate state of charge prediction model. Moreover, this work utilizes automotive grade lithium-based batteries for realistic outcomes in the electrified vehicle realm. The fourth chapter describes an advanced numerical model for computing vehicle energy usage performance. This work demonstrates the physical and mathematical theories involved, while building on the principles of Newton's second law of motion. Moreover, this chapter covers the equipment, software, and processes necessary for collecting the required data. Furthermore, a real world, on-road driving cycle provides for a quantification of accuracy. Multiple University of Kansas student project vehicles are then studied using parametric studies applicable to the operating requirements of the vehicles. Further investigation demonstrates the accuracy and trends associated with the advanced models presented in Chapters 2 and 3. Lastly, chapter 5 investigates the design and building of a graphical user interface (GUI) for controlling the models created in the previous three chapters. The chapter continues to outline the creation of a stand-alone GUI as well as instructions for implementation, usage, and data analysis

An object-oriented modelling method for evolving the hybrid vehicle design space in a systems engineering environment

A combination of environmental awareness, consumer demands and pressure from legislators has led automotive manufacturers to seek for more environmentally friendly alternatives while still meeting the quality, performance and price demands of their customers. This has led to many complex powertrain designs being developed in order to produce vehicles with reduced carbon emissions. In particular, within the last decade most of the major automotive manufactures have either developed or announced plans to develop one or more hybrid vehicle models. This means that to be competitive and o er the best HEV solutions to customers, manufacturers have to assess a multitude of complex design choices in the most e cient way possible. Even though the automotive industry is adept at dealing with the many complexities of modern vehicle development; the magnitude of design choices, the cross coupling of multiple domains, the evolving technologies and the relative lack of experience with respect to conventional vehicle development compounds the complexities within the HEV design space. In order to meet the needs of e cient and exible HEV powertrain modelling within this design space, a parallel is drawn with the development of complex software systems. This parallel is both from a programmatic viewpoint where object-oriented techniques can be used for physical model development with new equation oriented modelling environments, and from a systems methodology perspective where the development approach encourages incremental development in order to minimize risk. This Thesis proposes a modelling method that makes use of these new tools to apply OOM principles to the design and development of HEV powertrain models. Furthermore, it is argued that together with an appropriate systems engineering approach within which the model development activities will occur, the proposed method can provide a more exible and manageable manner of exploring the HEV design space.The exibility of the modelling method is shown by means of two separate case studies, where a hierarchical library of extendable and replaceable models is developed in order to model the di erent powertrains. Ultimately the proposed method leads to an intuitive manner of developing a complex system model through abstraction and incremental development of the abstracted subsystems. Having said this, the correct management of such an e ort within the automotive industry is key for ensuring the reusability of models through enforced procedures for structuring, maintaining, controlling, documenting and protecting the model development. Further, in order to integrate the new methodology into the existing systems and practices it is imperative to develop an e cient means of sharing information between all stakeholders involved. In this respect it is proposed that together with an overall systems modelling activity for tracking stakeholder involvement and providing a central point for sharing data, CAE methods can be employed in order to automate the integration of data.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Battery Second Use: A Framework for Evaluating the Combination of Two Value Chains

A Battery Second Use (B2U) strategy is the design and development of a battery system with the intention of having it serve two purposes: (1) the initial use in the vehicle and (2) another mobile or stationary application. An optimal battery second use strategy requires the design and use of the battery to maximize the value of the system over its entire extended life cycle. Within this thesis a framework is developed which allows the evaluation of tradeoffs along the operational second use value chain

12th EASN International Conference on "Innovation in Aviation & Space for opening New Horizons"

Epoxy resins show a combination of thermal stability, good mechanical performance, and durability, which make these materials suitable for many applications in the Aerospace industry. Different types of curing agents can be utilized for curing epoxy systems. The use of aliphatic amines as curing agent is preferable over the toxic aromatic ones, though their incorporation increases the flammability of the resin. Recently, we have developed different hybrid strategies, where the sol-gel technique has been exploited in combination with two DOPO-based flame retardants and other synergists or the use of humic acid and ammonium polyphosphate to achieve non-dripping V-0 classification in UL 94 vertical flame spread tests, with low phosphorous loadings (e.g., 1-2 wt%). These strategies improved the flame retardancy of the epoxy matrix, without any detrimental impact on the mechanical and thermal properties of the composites. Finally, the formation of a hybrid silica-epoxy network accounted for the establishment of tailored interphases, due to a better dispersion of more polar additives in the hydrophobic resin

Definition and verification of a set of reusable reference architectures for hybrid vehicle development

Current concerns regarding climate change and energy security have resulted in an increasing demand for low carbon vehicles, including: more efficient internal combustion engine vehicles, alternative fuel vehicles, electric vehicles and hybrid vehicles. Unlike traditional internal combustion engine vehicles and electric vehicles, hybrid vehicles contain a minimum of two energy storage systems. These are required to deliver power through a complex powertrain which must combine these power flows electrically or mechanically (or both), before torque can be delivered to the wheel. Three distinct types of hybrid vehicles exist, series hybrids, parallel hybrids and compound hybrids. Each type of hybrid presents a unique engineering challenge. Also, within each hybrid type there exists a wide range of configurations of components, in size and type. The emergence of this new family of hybrid vehicles has necessitated a new component to vehicle development, the Vehicle Supervisory Controller (VSC). The VSC must determine and deliver driver torque demand, dividing the delivery of that demand from the multiple energy storage systems as a function of efficiencies and capacities. This control component is not commonly a standalone entity in traditional internal combustion vehicles and therefore presents an opportunity to apply a systems engineering approach to hybrid vehicle systems and VSC control system development. A key non-­‐functional requirement in systems engineering is reusability. A common method for maximising system reusability is a Reference Architecture (RA). This is an abstraction of the minimum set of shared system features (structure, functions, interactions and behaviour) that can be applied to a number of similar but distinct system deployments. It is argued that the employment of RAs in hybrid vehicle development would reduce VSC development time and cost. This Thesis expands this research to determine if one RA is extendable to all hybrid vehicle types and combines the scientific method with the scenario testing method to verify the reusability of RAs by demonstration. A set of hypotheses are posed: Can one RA represent all hybrid types? If not, can a minimum number of RAs be defined which represents all hybrid types? These hypotheses are tested by a set of scenarios. The RA is used as a template for a vehicle deployment (a scenario), which is then tested numerically, thereby verifying that the RA is valid for this type of vehicle. This Thesis determines that two RAs are required to represent the three hybrid vehicle types. One RA is needed for series hybrids, and the second RA covers parallel and compound hybrids. This is done at a level of abstraction which is high enough to avoid system specific features but low enough to incorporate detailed control functionality. One series hybrid is deployed using the series RA into simulation, hardware and onto a vehicle for testing. This verifies that the series RA is valid for this type of vehicle. The parallel RA is used to develop two sub-­‐types of parallel hybrids and one compound hybrid. This research has been conducted with industrial partners who value, and are employing, the findings of this research in their hybrid vehicle development programs

Model Based Design Framework Development of a Hybrid Supervisory Controller for a P4 Parallel Hybrid Vehicle

The expected rise in the number of ECUs in an automotive based development environment, poses additional efficiency risk on developer time and code complexity. This thesis examines the design and validation of a Hybrid Supervisory Controller, developed for the University of Waterloo Alternative Fuels Team’s (UWAFT) retrofitted P4 parallel Chevrolet Blazer, in the EcoCAR Mobility Challenge competition. The controller, component models and I/O interaction layers are developed in a MathWorks Simulink environment. The framework discussed, is built to incorporate automation via a custom developed -Model-Configurator tool. Component models, and functional sub-systems are converted to masked library blocks within Simulink, that are populated via an object-oriented class in the MATLAB environment. This opens the possibility for custom environment data population, swapping of data for models while retaining underlying physics and setting up for SIL/HIL requirements testing without explicit/contemporary interaction with the Simulink environment. The advantages of this approach are discussed, along with explanation accompanying the software framework. The HSC incorporates interaction models of 9 stock vehicle, and on-board GM ECUs. The model spans full chassis longitudinal, and powertrain components. The functional controller incorporates 4 powertrain control layers - fault detection, vehicle state control, torque strategy and component level execution layers. The test environment switching time is reduced by >50%, and 86 controls requirements are tested over the course of 3 years. The test vehicle is tested at the Canadian Technical Center McLaughlin Advanced Technology Track (CTC MATT) where a non-standard drive cycle is used due to limitations posed by the COVID-19 pandemic. The vehicle robustly sustains a 91-minute city/highway drive, with a 24% improvement in fuel economy compared to stock. The vehicle however is short of its VTS targets which are attributed to the lack of engine start/stop functionality, and a thermally constrained battery pack. Those remain major design shortcomings and immediate powertrain improvements are proposed, and efficacy of a well-organized model are discussed

Sustainable Transportation Program 2011 Annual Report

Highlights of selected research and development efforts at Oak Ridge National Laboratory funded by the Vehicle Technologies Program, Biomass Program, and Hydrogen and Fuel Cells Program of the Department of Energy, Office of Energy Efficiency and Renewable Energy; and the Department of Transportation