Temperature is one of the most important parameters for the performance, safety, and aging of lithium-ion batteries and has been linked to all main barriers for widespread commercial success of electric vehicles. The aim of this thesis is to highlight the importance of temperature effects, as well as to provide engineering tools to study these. The mass transport phenomena of the electrolyte with LiPF6  in EC:DEC was fully characterized in between 10 and 40 °C and 0.5 and 1.5 M, and all mass transport properties were found to vary strongly with temperature. A superconcentrated electrolyte with LiTFSI in ACN was also fully characterized at 25 °C, and was found to have very different properties and interactions compared to LiPF6  in EC:DEC. The benefit of using the benchmarking method termed electrolyte masstransport resistivity (EMTR) compared to using only ionic conductivity was illustrated for several systems, including organic liquids, ionic liquids, solid polymers, gelled polymers, and electrolytes containing flame-retardant additives. TPP, a flame-retardant electrolyte additive, was evaluated using a HEV load cycle and was found to be unsuitable for high-power applications such as HEVs. A large-format commercial battery cell with a thermal management system was characterized using both experiments and a coupled electrochemical and thermal model during a PHEV load cycle. Different thermal management strategies were evaluated using the model, but were found to have only minor effects since the limitations lie in the heat transfer of the jellyroll. / Temperatur är en av de viktigaste parametrarna gällande ett litiumjonbatteris prestanda, säkerhet och åldring och har länkats till de främsta barriärerna för en storskalig kommersiell framgång för elbilar. Syftet med den här avhandlingen är att belysa vikten av temperatureffekter, samt att bidra med ingenjörsverktyg att studera dessa. Masstransporten för elektrolyten LiPF6  i EC:DEC karakteriserades fullständigt i temperaturintervallet 10 till 40 °C för LiPF6-koncentrationer på 0.5 till 1.5 M. Alla masstransport-egenskaper fanns variera kraftigt med temperaturen. Den superkoncentrerade elektrolyten med LiTFSI i ACN karakteriserades även den fullständigt vid 25 °C. Dess egenskaper och interaktioner fanns vara väldigt annorlunda jämfört med LiPF6  i EC:DEC. Fördelen med att använda utvärderingsmetoden elektrolytmasstransportresistivitet (EMTR) jämfört med att endast mäta konduktivitet illustrerades för flertalet system, däribland organiska vätskor, jonvätskor, fasta polymerer, gellade polymerer, och elektrolyter med flamskyddsadditiv. Flamskyddsadditivet TPP utvärderades med en hybridbils-lastcykel och fanns vara olämplig för högeffektsapplikationer, som hybridbilar. Ett kommersiellt storformatsbatteri med ett temperatur-kontrollsystem karakteriserades med b.de experiment och en kopplad termisk och elektrokemisk modell under en lastcykel utvecklad för plug-inhybridbilar. Olika strategier för kontroll av temperaturen utvärderades, men fanns bara ha liten inverkan på batteriets temperatur då begränsningarna för värmetransport ligger i elektrodrullen, och inte i batteriets metalliska ytterhölje. / <p>QC 20150522</p> / Swedish Hybrid Vehicle Center

This thesis evaluates a series hybrid electric drivetrain design for use in parking patrol vehicles. Due to the particular attributes of this application, it is proposed that the design would improve the energy efficiency of such a vehicle. The scheme is evaluated in depth through the use of electromagnetic transient simulation tools, which are used to create a highly accurate model of the vehicle. A prototype vehicle of the same design is built, and used to verify and improve the accuracy of the simulation model. The simulation model is then used to predict the energy efficiency of the series hybrid design for parking patrol. This simulation based design strategy is proposed as a method for more rapid and cost effective design of hybrid electric vehicles. / October 2007

This thesis evaluates a series hybrid electric drivetrain design for use in parking patrol vehicles. Due to the particular attributes of this application, it is proposed that the design would improve the energy efficiency of such a vehicle. The scheme is evaluated in depth through the use of electromagnetic transient simulation tools, which are used to create a highly accurate model of the vehicle. A prototype vehicle of the same design is built, and used to verify and improve the accuracy of the simulation model. The simulation model is then used to predict the energy efficiency of the series hybrid design for parking patrol. This simulation based design strategy is proposed as a method for more rapid and cost effective design of hybrid electric vehicles.

This thesis evaluates a series hybrid electric drivetrain design for use in parking patrol vehicles. Due to the particular attributes of this application, it is proposed that the design would improve the energy efficiency of such a vehicle. The scheme is evaluated in depth through the use of electromagnetic transient simulation tools, which are used to create a highly accurate model of the vehicle. A prototype vehicle of the same design is built, and used to verify and improve the accuracy of the simulation model. The simulation model is then used to predict the energy efficiency of the series hybrid design for parking patrol. This simulation based design strategy is proposed as a method for more rapid and cost effective design of hybrid electric vehicles.

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.

This research is focused on designing a new generation of CAD tools that could help a ”hybrid vehicle” designer with the design process to come up with better vehicle configurations. The conventional design process for any type of hybrid-electric vehicle would start from the vehicle performance criteria and continue by applying them to the physical models of different components of the vehicle. The final result would be strict and precise characteristics of all components in the vehicle; this scenario gives only one option for the desired vehicle. A new perspective is introduced in developing a new methodology in the art of design. This new method enables the designer to see a wider picture of what he is designing and have access to all his options and capabilities. The method is designed to help the designer ask the right questions about his design options, intelligently guide him through the design process by squeezing the space of solutions and take him to the final designed product. The new methodology is implemented in this research with the following capabilities: 1. The proposed tool allows the designer to choose any arbitrary set of variable to be known and leave the rest as the ones to be solved for; either they are vehicle component characteristic variables or performance measures. This provides a great amount of flexibility and success in designing a vehicle from any available information about it. 2. Instead of starting from single values, the new tool can work with a range of possible values for the known variables and suggest range of feasible values for the unknown variables. This provides the capability of refining the design even further and performing sensitivity analysis. 3. The proposed tool is a package that offers both design and simulation capabilities. It includes analytical performance simulation as well as simulation with arbitrary drive cycles and engine controllers. 4. Capability of 1D, 2D and 3D representation of any arbitrary set of design variables in the solution space. The idea is implemented in a pilot version software package for vehicle design.

System level parametric design of hybrid electric vehicles involves estimation of the power ratings as well as the values of certain parameters of the components, given the values of the performance parameters. The design is based on certain mathematical equations or ‘design rules’, which relate the component parameters and the performance parameters. The flow of the design algorithm is uni-directional and fixed, and cannot be altered. This thesis proposes a new method for such parametric design, called omni- directional design, which does not have a fixed sequence like the conventional design, but can start with any parameters of the designer’s choice. The designer is also able to specify the input parameters over a range, instead of a point (one, fixed value) input. Scenarios having a point input, but values of an output which can vary over a range for the point input, can also be studied.

Power-split hybrid-electric vehicles (HEVs) provide two power paths between the internal combustion (IC) engine and the driven wheels through gearing and electric machines (EMs) composing an electrically variable transmission (EVT). EVTs allow IC engine control such that rotational speed is independent of vehicle speed at all times. By breaking the rigid mechanical connection between the IC engine and the driven wheels, EVTs allow the IC engine to operate in the most efficient region of its characteristic brake specific fuel consumption (BSFC) map. If the most efficient IC engine operating point produces more power than is requested by the driver, the excess IC engine power can be stored in the energy storage system (ESS) and used later. Conversely, if the most efficient IC engine operating point does not meet the power request of the driver, the ESS delivers the difference to the wheels through the EMs. Therefore with an intelligent supervisory control strategy, power-split architectures can advantageously combine traditional series and parallel power paths. In the first part of this work, two different power-split HEV powertrains are compared using a two-term cost function and steady-state backward-looking simulation (BLS). BLS is used to find battery power management strategies that result in minimized fuel consumption over a user-defined drive-cycle. The supervisory control strategy design approach amounts to an exhaustive search over all kinematically admissible input operating points, leading to a minimized instantaneous cost function. While the approach provides a valuable comparison of two architectures, non-ideal engine speed fluctuations result. Therefore, in the second part of the work, two approaches for designing control strategies with refined IC engine speed transitions are investigated using high-fidelity forward-looking simulation (FLS). These two approaches include: i) smoothing the two-term cost function optimization results, and ii) introducing a three-term cost function. It is found that both achieve operable engine speed transitions, and result in fuel economy (FE) estimates which compare well to previous BLS results. It is further found that the three-term cost function finds more efficient operating points than the smoothed two-term cost function approach. From the investigations carried out in parts one and two of this work, a two-phase control strategy development process is suggested where control strategies are generated using efficient steady-state BLS models, and then further tested and verified in high-fidelity FLS models. In conclusion, the FLS results justify the efficacy of the two-phased process, suggesting rapid and effective development of implementable power-split HEV supervisory control strategies.

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.

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