No description available.

A survey of the existing literature indicates that optimization on the power management logic of hybrid electric vehicle is mostly performed after the design of the powertrain architecture or the power source components are finalized. The goal of this research is to utilize Multidisciplinary Design Optimization (MDO) to automate and optimize the vehicle’s powertrain component sizes, while simultaneously determining the optimal power management logic in developing the most cost-effective system solution. A generic, modular, and flexible vehicle model utilizing a backward-looking architecture is created using scalable powertrain components. The objective of the research work is to study the energy efficiency of the vehicle system, where the dynamics of the vehicle is not of concern; a backward-looking architecture could be used to compute the power consumption and the overall efficiency accurately while minimizing the required computing resource. An optimization software platform utilizing multidisciplinary design optimization approach is implemented containing the generic vehicle model and an optimizer of the user’s choice. The software model is created in the MATLAB/Simulink environment, where the optimization code and the powertrain component properties are implemented using m-files, and the power consumption calculations of the vehicle system are performed in Simulink. Furthermore, a feature-based optimization technique is developed with the motivation of significantly reducing the simulation run-time. To demonstrate the capabilities of the developed approach and contributions of the research, two optimization case studies are undertaken: (i) series hybrid electric vehicles, and (ii) police vehicle anti-idling system. As the first case study, a plug-in battery-only series hybrid electric vehicle with similar power components as the Chevrolet Volt is created, where the battery size and the power management logic are simultaneously optimized. The objective function of the optimizer is defined from the financial cost perspective, where the objective is to minimize the initial cost of batteries, gasoline and electricity consumption over a period of five years, and the carbon tax as a penalty function for fuel emissions. The battery-only series hybrid electric vehicle is subsequently extended to include ultracapacitors, and the optimization process is expanded to the rest of the powertrain components and power management logic. A comparison between the optimization algorithms found that only genetic algorithm (GA) was capable of finding the optimal solution during a full simulation, while simulated annealing and pattern search were not able to converge to any solution after a 24-hour period. A comparison between the full genetic algorithm optimization and the feature-based (FB) method with secondary optimization found that although the final cost function of the FB methodology is higher than that of the full GA optimization, the total simulation run-time is approximately ten times less using the FB method. The behaviour of the solutions found via both methods exhibited almost identical characteristics, further confirming the validity of the feature-based methodology. Finally, a benchmarking comparison found that with more accurate manufacturers’ component data and additional appropriate performance requirements, the proposed software platform will be capable of predicting a solution that is comparable to the Chevrolet Volt. The second case study involves optimizing an anti-idling system for police vehicles using the same optimization algorithm and generic vehicle model. The goal of the optimization study is to select an additional battery and determine the power management logic to reduce the engine idling time of a police vehicle. It is found that depending on the SOC threshold, the duration of time over which the engine is activated varies in a non-linear fashion, where local minima and maxima exist. A design study confirmed that by utilizing the anti-idling system, significant cost reduction can be realized when compared to one without the anti-idling system. A comparison between the various optimization algorithms showed that the feature-based optimization can obtain a relatively accurate solution while reducing simulation time by approximately 90%. This significant reduction in simulation time warrants the feature-based optimization technique a powerful tool for vehicle design. Due to the high cost of the electrical energy storage components, it is currently still more cost-effective to use the fossil fuel as the primary energy source for transportation. However, given the rise of fuel cost and the advancement in the electrical energy storage technology, it is inevitable that the cost of the electrical and chemical energy storage method will reach a balance point. The proposed optimization platform allows the user the capability and flexibility to obtain the optimal vehicle solution with ease at any given time in the future.

Dissertation (Ph.D.)--University of Toledo, 2009. / Typescript. "Submitted as partial fulfillment of the requirements for the Doctor of Philosophy degree in Mechanical Engineering." Bibliography: leaves 203-209.

Thesis (M.A.) - Carleton University, 2009. / Includes bibliographical references (p.68-71). Also available in electronic format on the Internet.

No description available.

Lithium-ion batteries designed for use in heavy-duty hybrid vehicles are continuously improved in terms of performance and longevity, but they still have limitations that need to be considered when developing new hybrid vehicles.                The aim of this thesis has been to study and evaluate potential test and analysis methods suitable for being used in the design process when maximizing lifetime and utilization of batteries in heavy-duty hybrid vehicles. A concept for battery cell cycling on vehicles has been evaluated. The work included development of test equipment, verification of hardware and software as well as an extended period of validation on heavy-duty trucks. The work showed that the concept has great potential for evaluating strategies for battery usage in hybrid vehicles, but is less useful for accelerated aging of battery cells.                             Battery cells encapsulated in flexible packaging material have been investigated with respect to the durability of the encapsulation in a demanding heavy-duty hybrid truck environment. No effect on water intrusion was detected after vibration and temperature cycling of the battery cells.                    Aging of commercial battery cells of the type lithium manganese oxide - lithium cobalt oxide / lithium titanium oxide (LMO-LCO/LTO) was investigated with different electrochemical methods to gain a deeper understanding of the origin of performance deterioration, and to understand the consequences of aging from a vehicle manufacturer's perspective. The investigation revealed that both capacity loss and impedance rise were largely linked to the positive electrode for this type of battery chemistry.                           Postmortem analysis of material from cycle-aged and calendar-aged battery cells of the type LMO-LCO/LTO and LiFePO4/graphite was performed to reveal details about aging mechanisms for those cell chemistries. Analysis of cycle-aged LMO-LCO/LTO cells revealed traces of manganese in the negative electrode and that the positive electrode exhibited the most severe aging. Analysis of cycle-aged LFP/graphite cells revealed traces of iron in the negative electrode and that the negative electrode exhibited the most severe aging. / Litiumjonbatterier anpassade för användning i tunga hybridfordon förbättras kontinuerligt med avseende på prestanda och livslängd men har fortfarande begränsningar som måste beaktas vid utveckling av nya hybridfordon.                 Syftet med denna avhandling har varit att studera och utvärdera potentiella prov- och analysmetoder lämpliga för användning i arbetet med att maximera livslängd och utnyttjandegrad av batterier i tunga hybridfordon.                               Ett koncept för battericykling på fordon har utvärderats. Arbetet innefattade utveckling av testutrustning, verifiering av hårdvara och mjukvara samt en längre periods validering på lastbilar. Arbetet har visat att konceptet har stor potential för utvärdering av strategier för användandet av batterier i hybridfordon, men är mindre användbar för åldring av batterier.                                Batterier kapslade i flexibelt förpackningsmaterial har undersökts med avseende på kapslingens hållbarhet i en krävande hybridlastbilsmiljö. Ingen påverkan på fuktinträngning kunde påvisas efter vibration och temperaturcykling av de testade battericellerna.                     Åldring av kommersiella battericeller av typen litiummanganoxid - litiumkoboltoxid/litiumtitanoxid (LMO-LCO/LTO) undersöktes med olika elektrokemiska metoder för att få en djupare förståelse för prestandaförändringens ursprung och för att förstå konsekvenserna av åldrandet ur en fordonstillverkares användarperspektiv. Undersökningen visade att både kapacitetsförlust och impedanshöjning till största delen var kopplat till den positiva elektroden för denna batterityp.                  Post-mortem analys av material från cyklade och kalenderåldrade kommersiella battericeller av typen LMO-LCO/LTO och LiFePO4/grafit utfördes för att avslöja detaljer kring åldringsmekanismerna för dessa cellkemier. Vid analys av cyklade LMO-LCO/LTO celler påvisades mangan i den negativa elektroden samt uppvisade den positiva elektroden kraftigast åldring. Vid analys av cyklade LFP/grafit celler påvisades järn i den negativa elektroden samt uppvisade den negativa elektroden kraftigast åldring. / <p>QC 20140520</p>

A proposed hybrid electric marine vehicle was modeled in MATLAB Simulink and SimPowerSystems. Models for each of the individual propulsion components were developed and incorporated into a complete hybrid electric propulsion model. A vessel resistance model was created to support vessel performance and energy requirement evaluation. The model incorporates data based on the ship principal parameters and hull form. A rule-based supervisory controller for the proposed vessel was constructed. It is an amalgamation of control strategies of three vehicle architectures: electric vehicle, fuel cell electric vehicle, and hybrid electric vehicle (HEV). The complete model of the hybrid electric propulsion, control, and resistance subsystems was simulated on a dSPACE hardware-in-the-loop platform. For each simulation, the energy storage system (ESS) state of charge, station keeping/cruising mode, HEV assist, Beaufort number, current speed, true wind angle, and hotel load were specified. From the simulations, it was demonstrated that using a 30% ESS assisted HEV mode results in reduced emissions and fuel consumption as compared to a conventional vessel powertrain mode, supporting the case for plug-in hybrid electric vessels. A larger capacity ESS has the potential to reduce emissions and fuel consumption further, depending on ship usage. The basic rule-based supervisory controller proved functional for facilitating adequate power flows; however, further development is needed to improve efficiency and the mode selection process. / Graduate / 0548

Commercially available Hybrid Electric Vehicles (HEVs) have been around for more than ten years. However, their market share remains small. Focusing only on the improvement of fuel economy, the design tends to reduce the size of the internal combustion engine in the HEV, and uses the electrical drive to compensate for the power gap between the load demand and the engine capacity. Unfortunately, the low power density and the high cost of the combined electric motor drive and battery packs dictate that the HEV has either worse performance or much higher price than the conventional vehicle. In this research, a new design philosophy for parallel HEV is proposed, which uses a full size engine to guarantee the vehicle performance at least as good as the conventional vehicle, and hybridizes with an electrical drive in parallel to improve the fuel economy and performance beyond the conventional cars. By analyzing the HEV fuel economy versus the increasing of the electrical drive power on typical driving conditions, the optimal hybridization electric power capacity is determined. Thus, the full size engine HEV shows significant improvement in fuel economy and performance, with relatively short cost recovery period. A new control strategy, which optimizes the fuel economy of parallel configured charge sustained hybrid electric vehicles, is proposed in the second part of this dissertation. This new approach is a constrained engine on-off strategy, which has been developed from the two extreme control strategies of maximum SOC and engine on-off, by taking their advantages and overcoming their disadvantages. A system optimization program using dynamic programming algorithm has been developed to calibrate the control parameters used in the developed control strategy, so that the control performance can be as close to the optimal solution as possible. In order to determine the sensitivity of the new control strategy to different driving conditions, a passenger car is simulated on different driving cycles. The performances of the vehicle with the new control strategy are compared with the optimal solution obtained on each driving condition with the dynamic programming optimization. The simulation result shows that the new control strategy always keeps its performance close to the optimal one, as the driving condition changes.

A survey of the existing literature indicates that optimization on the power management logic of hybrid electric vehicle is mostly performed after the design of the powertrain architecture or the power source components are finalized. The goal of this research is to utilize Multidisciplinary Design Optimization (MDO) to automate and optimize the vehicle’s powertrain component sizes, while simultaneously determining the optimal power management logic in developing the most cost-effective system solution. A generic, modular, and flexible vehicle model utilizing a backward-looking architecture is created using scalable powertrain components. The objective of the research work is to study the energy efficiency of the vehicle system, where the dynamics of the vehicle is not of concern; a backward-looking architecture could be used to compute the power consumption and the overall efficiency accurately while minimizing the required computing resource. An optimization software platform utilizing multidisciplinary design optimization approach is implemented containing the generic vehicle model and an optimizer of the user’s choice. The software model is created in the MATLAB/Simulink environment, where the optimization code and the powertrain component properties are implemented using m-files, and the power consumption calculations of the vehicle system are performed in Simulink. Furthermore, a feature-based optimization technique is developed with the motivation of significantly reducing the simulation run-time. To demonstrate the capabilities of the developed approach and contributions of the research, two optimization case studies are undertaken: (i) series hybrid electric vehicles, and (ii) police vehicle anti-idling system. As the first case study, a plug-in battery-only series hybrid electric vehicle with similar power components as the Chevrolet Volt is created, where the battery size and the power management logic are simultaneously optimized. The objective function of the optimizer is defined from the financial cost perspective, where the objective is to minimize the initial cost of batteries, gasoline and electricity consumption over a period of five years, and the carbon tax as a penalty function for fuel emissions. The battery-only series hybrid electric vehicle is subsequently extended to include ultracapacitors, and the optimization process is expanded to the rest of the powertrain components and power management logic. A comparison between the optimization algorithms found that only genetic algorithm (GA) was capable of finding the optimal solution during a full simulation, while simulated annealing and pattern search were not able to converge to any solution after a 24-hour period. A comparison between the full genetic algorithm optimization and the feature-based (FB) method with secondary optimization found that although the final cost function of the FB methodology is higher than that of the full GA optimization, the total simulation run-time is approximately ten times less using the FB method. The behaviour of the solutions found via both methods exhibited almost identical characteristics, further confirming the validity of the feature-based methodology. Finally, a benchmarking comparison found that with more accurate manufacturers’ component data and additional appropriate performance requirements, the proposed software platform will be capable of predicting a solution that is comparable to the Chevrolet Volt. The second case study involves optimizing an anti-idling system for police vehicles using the same optimization algorithm and generic vehicle model. The goal of the optimization study is to select an additional battery and determine the power management logic to reduce the engine idling time of a police vehicle. It is found that depending on the SOC threshold, the duration of time over which the engine is activated varies in a non-linear fashion, where local minima and maxima exist. A design study confirmed that by utilizing the anti-idling system, significant cost reduction can be realized when compared to one without the anti-idling system. A comparison between the various optimization algorithms showed that the feature-based optimization can obtain a relatively accurate solution while reducing simulation time by approximately 90%. This significant reduction in simulation time warrants the feature-based optimization technique a powerful tool for vehicle design. Due to the high cost of the electrical energy storage components, it is currently still more cost-effective to use the fossil fuel as the primary energy source for transportation. However, given the rise of fuel cost and the advancement in the electrical energy storage technology, it is inevitable that the cost of the electrical and chemical energy storage method will reach a balance point. The proposed optimization platform allows the user the capability and flexibility to obtain the optimal vehicle solution with ease at any given time in the future.

Thesis (M.S.)--West Virginia University, 1999. / Title from document title page. Document formatted into pages; contains viii, 69 p. : ill. Includes abstract. Includes bibliographical references (p. 68-69).