Electric Vehicles (EVs) have gained acceptance as low or zero emission means of transportation. This thesis deals with the design of a battery cell testing platform and Lithium-Ion (Li-Ion) battery modeling for EVs. A novel regenerative cell testing platform is developed for cell cycling applications. A 300 W - 5 V cell cycler consisting of a buck and a boost converter is designed. Furthermore, a novel battery modeling approach is proposed to accurately predict the battery performance by dynamically updating the model parameters based on the battery temperature and State of Charge (SOC). The comparison between the experimental and the model simulation results of an automotive cell under real-world drive-cycle illustrates 96.5% accuracy of the model. In addition, the model can be utilized to assess the long-term impact of battery impedance on performance of EVs under real-world drive-cycles.

This thesis describes and evaluates the conversion of a conventional gasoline powered all-terrain vehicle (ATV) to an electric ATV. Preliminary studies are performed to obtain initial power and torque requirements for the vehicle. A detailed simulation model of the mechanical load is written and compared to manufacturer supplied data. The load model is then combined with a comprehensive electronic drive and motor simulation using an electromagnetic transient simulation program (PSCAD). A prototype of the vehicle is constructed by selecting the main components, an electric traction motor, batteries and a custom motor drive, using the simulation results. The results of both the simulation and prototypes are compared and evaluated.

Electric Vehicles (EVs) have gained acceptance as low or zero emission means of transportation. This thesis deals with the design of a battery cell testing platform and Lithium-Ion (Li-Ion) battery modeling for EVs. A novel regenerative cell testing platform is developed for cell cycling applications. A 300 W - 5 V cell cycler consisting of a buck and a boost converter is designed. Furthermore, a novel battery modeling approach is proposed to accurately predict the battery performance by dynamically updating the model parameters based on the battery temperature and State of Charge (SOC). The comparison between the experimental and the model simulation results of an automotive cell under real-world drive-cycle illustrates 96.5% accuracy of the model. In addition, the model can be utilized to assess the long-term impact of battery impedance on performance of EVs under real-world drive-cycles.

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>

This thesis describes and evaluates the conversion of a conventional gasoline powered all-terrain vehicle (ATV) to an electric ATV. Preliminary studies are performed to obtain initial power and torque requirements for the vehicle. A detailed simulation model of the mechanical load is written and compared to manufacturer supplied data. The load model is then combined with a comprehensive electronic drive and motor simulation using an electromagnetic transient simulation program (PSCAD). A prototype of the vehicle is constructed by selecting the main components, an electric traction motor, batteries and a custom motor drive, using the simulation results. The results of both the simulation and prototypes are compared and evaluated.

From the electrical engineering perspective, this thesis addresses the design and implementation of the conversion process from a hybrid electric to a full function electric vehicle (FFEV). The architecture selection process and main components of an electric vehicle (EV) are described, and an exhaustive literature review on the controller area network (CAN) is presented. The electrical and control system integration strategy is explained, along with the model-based algorithm programmed into the vehicle integration module (VIM). Emulating electronic control units (ECUs) from the original powertrain and controlling additional ones for the electrical drivetrain through CAN bus, along with keeping the same functionalities of a typical production vehicle makes this vehicle conversion similar to a factory built model. Finally, the tests and results originating from this conversion to a full electric powertrain are discussed. The vehicle features a 83.5 kWh Li-ion battery built in-house, resulting in an estimated range of 482 km.

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.

Battery Electric Vehicles and Plug-in Hybrid Vehicles are increasingly becoming more popular in recent years. Stricter regulations from government agencies to curb emissions and reduce impact on climate have led to automobile makers adopt electric powertrains. Eco-Routing is one such method to reduce energy usage in personal transport. EcoRouting is a methodology that determines the route with the least energy consumption between two points. Standard navigation systems often determine the shortest or the fastest route, emphasizing travel time. EcoRouting considers an alternative criterion - energy consumption. In this thesis, an automation methodology is presented that determines the EcoRoute among given route alternatives based on route distance, speed limits, road grades, traffic signs, driver aggression and the powertrain. There are three major objectives in this thesis: Developing the automation methodology for the determination of EcoRoute for use in on-board applications, validating the EcoRouting methodology on actual driving conditions and studying the impact of traffic on the choice of EcoRoute. The automation methodology has been developed on the Android framework for use with on-board applications on Android mobile devices. The automation methodology used to conduct sensitivity studies show that factors such as driver aggression, distance and conditional stops impact energy consumption. The comparison of results of simulation using the automation methodology against results from actual driving to validate the methodology on actual driving conditions show that transient traffic conditions can have significant impact on energy consumption. Finally, route energy consumptions for various traffic conditions are estimated using simulation to understand the impact of traffic on energy consumption and EcoRoute choice. Results that are obtained show that apart from traffic affecting the energy consumption, travel times can have an impact on choice of EcoRoute. / Master of Science / Government agencies have been introducing tighter regulations in order to improve fuel economy and reduce emissions. These regulations are targeted at reducing the impact of vehicle usage on climate. Automobile manufacturers have increasingly adopted electric powertrains to meet these regulations. Battery Electric Vehicles and Plug-in Hybrid Vehicles are more popular than ever. Other methods in reducing environmental impact by automobiles are also being conducted. EcoRouting is one such method. EcoRouting determines the route that consumes the least energy between two locations. EcoRouting requires no modifications to be done on the vehicle or its powertrain. A methodology has been developed in this thesis that takes into account various factors such as traffic signs, speed limits, road grades, powertrain and driver aggression to determine the route that consumes the least energy. Research in this thesis has been divided into three major parts: development of the automation methodology, validating the methodology for actual driving conditions and understanding the impact of traffic on energy consumption. Results of case studies show that the input parameters affect energy consumption significantly. Traveling speeds affect the energy consumption and since transient traffic conditions can affect traveling speeds, transient traffic conditions can have a significant impact on energy consumption. Since energy consumption alone is not considered in determining the EcoRoute and the travel times are also considered so as to not inconvenience the user, traffic conditions impact the choice of EcoRoute both due to differences in energy consumption and travel time.

The lithium ion battery is today mainly used in cell phonesand laptops. In the future, this kind of battery might beuseful in hybrid electric vehicles as well. In this work, the main focus has been to gain more knowledgeabout the lithium ion battery in the hybrid electric vehicle(HEV) and more precisely to examine what processes of thebattery that are limiting at HEV currents. Both experiments andmathematical modelling have been used. In both cases, highrate, pulsed currents typical for the HEV, have been used. Two manuscripts have been written. Both of them concern thebehaviour of the battery at HEV load, but from different pointsof view. The first one concerns the electrochemical behaviourof the battery at different ambient temperatures. Theexperimental results of this paper were used to validate amathematical model of a Li-ion battery. Possiblesimplifications of the model were identified. In this work itwas also concluded that the mass transfer of the electrolyte isthe main limiting process within the battery. The mass transferof the electrolyte was further studied in the second paper,where the concentration of lithium ions was measured indirectlyusing in situ Raman spectroscopy. This study showed that themathematical description of the mass transfer of theelectrolyte is not complete. One main reason of this issuggested to be the poor description of the physical parametersof the electrolyte. These ought to be further studied in orderto get a better fit between concentration gradients predictedby experiments and model respectively.

Power management strategies have impacts on fuel economy, greenhouse gasses (GHG) emission, as well as effects on the durability of power-train components. This is why different off-line and real-time optimal control approaches are being developed. However, real-time control seems to be more attractive than off-line control because it can be directly implemented for managing power and energy flow inside an actual vehicle. One interesting illustration of these power management strategies is the model predictive control (MPC) based algorithm. Inside an MPC, a cost function is optimized while system constraints are validated in real time. The MPC algorithm relies on dynamic models of the vehicle and the battery. The complexity and accuracy of the battery model are usually neglected to benefit the development of new cost functions or better MPC search algorithms. In fact, the literature does not deal with the impact of the battery model on MPC. This is why this Ph.D. dissertation evaluates the impact of different battery models of a plug-in hybrid electric vehicle (PHEV) through a sensitivity analysis to reach optimal performance for an MPC. The required fidelity of the battery might depend on different factors:the prediction horizon also called look-ahead step time the vehicle states update time the vehicle model step time the objective function The results of simulations show that higher fidelity model improves the capability to predict accurately the battery aging. As the battery pack is currently one of the most expensive components of an electric vehicle and lithium is a limited natural resource, being able to manage precisely the battery aging is a crucial point for both the automotive company and the battery manufacturer. Another important aspect highlighted by this PhD dissertation is that higher battery fidelity model reduces the possibility to violate the SoC constraint, which is greatly desirable. In fact, this constraint is usually defined by battery manufacturers for safety and battery aging management reasons. Last but not least, it has been proven that the impact of the battery modeling for the MPC controller depends on what the objective function aims to optimize. For instance, battery modeling have limited impact if the objective function takes into account the fuel consumption but far more for if it considers the battery degradation.