The transport sector is a major cause of emissions both in Sweden and globally. This master thesis aims to develop a model for estimating emissions from heavy transport on a specific route. The emissions can be used in a route planning software and help the driver choose a route that contributes to reduced emissions. The methodology was to investigate attributes, like vehicle-related attributes and topography, and their impact on transport emissions. The carbon dioxide, methane and nitrous oxide emissions were converted into carbon dioxide equivalents, which were incorporated as one cost together with a precalculated driving time as a second cost in a multi objective function used for route planning. Different tests were conducted to investigate the accuracy and the usability of the model. First, a validation test was performed, where the optimized routes were analyzed. The test showed that the model was more likely to choose a shorter route in general. The fuel consumption values largely met expectations towards generic values and measurements, that were gathered from research. A second test of the model made use of the driving time combined with the emissions in a multi objective function. In this test, a weighting coefficient was varied and analyzed to understand the possibility to find a value of the coefficient for the best trade-off. The result showed that the model generates different solutions for different coefficients and that it is possible to find a suitable trade-off between the driving time and emissions. Therefore, this study shows that there is a possibility to combine emission with other objectives such as driving time for route optimization. Finally, a sensitivity analysis was performed, where attribute factors and assumptions were varied to see how sensitive they were and, in turn, how much a change would impact the calculated emissions. The result from the sensitivity analysis showed that the changes in topography-attributes had less impact than changes on vehicle-related attributes. In conclusion, this thesis has built a foundation for route planning, based on the environmental aspect, for heavy transports.

Bakgrund & Problem: Transport och distribution utgör grundläggande aktiviteter i ett transportföretag, såsom en 3PL-aktörs, verksamhet. I denna verksamhet är tunga transporter vanligt förekommande vilket utgör en betydande del av världens totala koldioxidutsläpp. Samtidigt som bränsleförbrukning står för en stor del av ett åkeris totala kostnader driver det även CO2-utsläpp i en redan, sett ur ett miljömässigt perspektiv, ansträngd värld. Att på sikt reducera dem globala CO2-utsläppen kommer kräva en omställning av transportsektorn och en övergång från fossila bränslen till mer förnyelsebara. För det enskilda åkeriet kan minskad bränsleförbrukning sänka kostnaderna samtidigt som det är fördelaktigt för miljön då det leder till minskade CO2-utsläpp. Vad driver då bränsleförbrukningen i ett åkeri? I denna studie ligger fokus främst på sparsam körning, transportplanering och teknologi som de faktorer som påverkar bränsleförbrukningen. I sammanhanget är även val av bränsle relevant men denna faktor har analyserats separat då det snarare är en faktor som driver CO2-utsläpp än bränsleförbrukningen i sig. Syfte: Syftet med denna studie är att studera ett urval av transportföretaget GDL:s åkerier och dess verksamhet med primärt fokus på bränsleförbrukning och CO2-utsläpp. Ambitionen vid arbetets slut är att kunna betygsätta åkeriernas verksamhet med utgångspunkt i deras bränsleförbrukning och de faktorer som driver den. Studien syftar även till att klargöra maktförhållandet mellan uppdragsgivare, som GDL, och åkerier. Metod: Studien tillämpar ett positivistiskt vetenskapligt synsätt med abduktion som angreppssätt. Baserat på de frågeställningar som studeras i detta arbete har en kvalitativ forskningsmetod applicerats överlag med små inslag av kvantitativa aspekter. Slutsats: De faktorer som huvudsakligen driver bränsleförbrukning är sparsam körning, transportplanering och teknologi. Sparsam körning är den faktor som denna studie bedömer ha störst påverkan och en fullständig implementering kan resultera i en bränslereduktion på 10-30 5(95) procent. Förutom mängden bränsle som förbrukas har även val av bränsle möjligheten att påverka företag positivt, främst miljömässigt men även ekonomiskt, där alternativa bränslen är huvudsakligt fokus. I denna studie hanteras bränslen som är förekommande inom studiens åkerier och bland dessa har HVO klart lägst CO2-utsläpp. Inflytandet från större aktörer, som GDL, är i nuläget svårt att precisera och varierar mellan åkerier. GDL:s position på marknaden borde, om så önskas, möjliggöra att ett större inflytande utövas gentemot de mindre aktörer som till stor del kör åt GDL. / Background & Problem: Transportation and distribution, such as 3PL, pose an essential part of a logistics company’s scope of duties; especially heavy transports, which account for a big part of the worldwide CO2-emissions, are an essential part of the business. Whilst fuel consumption makes up the majority of a company’s total consecutive expenses, it also augments carbon dioxide emission in our already flawed world. Therefore, the aim in the long run is a readjustment in the transport sector which includes the transition from fossil fuels towards renewable energy sources as well as the reduction of fuel consumption in general. This is also in the interest of the distribution companies, as they thereby can save expenses and reduce their ecological footprint at the same time. Yet, what determines the fuel consumption of a distribution company? To decry that, this study will primarily focus on eco-driving, route planning as well as technology as the main drivers of fuel consumption. It hereby is necessary to consider the chosen kind of fuel as an important factor regarding the CO2-emissions; this, however, will be analyzed separately. Purpose: The purpose of this paper is to study a selection distribution companies that primarily work on behalf of GDL, to examine which factors drive fuel consumption and CO2 emissions 6(95) within these companies. This papers ambition is to fairly evaluate the distribution companies and grade them accordingly, based on factors that drive fuel consumption and CO2 emissions. Additionally, this paper also aims to clarify the power structure between outsourcers, such as GDL, and their distributors. Method: This paper applies a positivistic scientific view with abduction as an approach. Based on this papers research questions it was determined that a qualitative research method should be applied throughout the study, with minor quantitative elements. Conclusions: The main factors for fuel consumption are parsimonious driving, route planning as well as technology. Hereby, frugal driving was ranked as the most important one as it can lead to a saving of 10-30 percent. Furthermore, the amount of used fuel can be positively influenced through the choice of certain fuel types. This has economical as well as ecological effects; the study focusses on renewable fuels, such as HVO, which has by far the lowest CO2- emissions amongst the fuels that were drawn into consideration. Influence by bigger actors, such as GDL, makes it hard to determine between different companies’ standings, as GDL’s position directly influences their smaller distributers.

This master thesis is part of a bigger project issued by AVL with the purpose to design a high pressure compression ignition fuel system for their single cylinder test cell at their facility in Södertälje. Typically compression-ignition fuel tests are being run within an operating pressure range of 500-2400 bar, but this system has to be able to run with pressures up to 3500 bar. The project was intended to be carried out by two participants where this master thesis covers the evaluation of how fuel consumption rates shall be measured in the system described above as well as how the fuel shall be conditioned. The selected concept for measuring fuel consumption rate was based on measuring the mass flow on the low-pressure side of the system with a Coriolis flowmeter. The chosen temperature sensor for monitoring the temperature on the high-pressure side was a K-type thermocouple which would be directly connected to the fuel rail in the system. A bleeder was selected on the basis that it had been used in one of AVL's old test cells. A heat exchanger could not be chosen. However a rough estimation of the capacity needed for a heat exchanger was calculated for future reference. The methodology used to develop a concept was based on the engineering project process taught to students at Karlstad University. First a project plan was made followed by a solution-independently expressed product specification including a specification of requirements and QFD-matrix. Several concepts were generated for measuring the fuel consumption by evaluating different measuring principles, available components, possible positions of the components within the system and combinations with different fuel supply concepts. Less extensive methods were used for the remaining tasks in the detailed engineering phase of the project. The concepts were compared using Pugh's analysis and a concept was selected in collaboration with AVL. The majority of the objectives for this master thesis could be successfully carried out. The documentation and drawings requested by the client, manufacturing of the system, implementation and validation into the test cell could not be done due to lack of time. This, along with the selection of a heat exchanger and low-pressure thermocouple was left for future work.

The impact of air travel on the climate, along with its increasing share in CO2 emissions have raised the demand for sustainable air travel solutions. The current aircraft technologies have seen significant improvement throughout the years. Although, the rate at which new aircraft technologies are developed can not keep up with the increased demand for air travel. Hence, a different approach to reduce the aviation’s impact on climate can be achieved by optimizing the vertical flight path in order to reduce the fuel consumption, i.e. using dynamic programming. Upon departure, an optimization of the vertical flight path is initiated and an optimal flight plan is suggested to the flight crew.  The fuel saving produced by the optimal flight plan is a potential saving that can only be fully achieved if the flight crew chose to fly according to the optimized flight path. However, restrictions from the Air Traffic Control, as well as the flight crew’s willingness to follow the optimized flight path can affect the achieved saving. Hence, a tool is developed in order to compute trip fuel consumption from post-flight data obtained from the Automatic Dependent Surveillance-Broadcast (ADS-B) surveillance technology. A method to identify the start and end positions of cruise segments is successfully implemented. Two methods of calculating the fuel are implemented and compared. The first method is based on simulating the actual flight, which uses the same performance model as for the simulation of the operational flight plan trip and optimized trip. The second method is based on utilizing the ADS-B data to obtain the aircraft speed which in return can be used as a parameter to obtain the fuel flow of the aircraft, hence the trip is not simulated. The results reveals that the simulation method produces flight trajectories that are comparable to the operational and optimized flight plans since they use the same model structure. However, using ADS-B data to obtain fuel consumption represents the actual flight trajectory more accurately.  Furthermore, an optimization algorithm based on the onboard Flight Management Computer is implemented. According to the results, the FMC optimization offers a sufficient optimization of the cruise phase, when compared to the OFP trip, however performs worse than the dynamic programming, which provides a global optimal solution. / Flygresornas inverkan på klimatet, tillsammans med dess ökande andel av CO2-utsläppen, har ökat kraven på hållbara flygplanslösningar. Den nuvarande flygplansteknologin har genomgått betydande förbättringar genom åren. Men takten för vilken ny flygplansteknik utvecklas kan inte hålla jämna steg med den ökade efterfrågan på flygresor. Däremot kan ett annat tillvägagångssätt för att minska flygets påverkan på klimatet uppnås genom att optimera den vertikala flygvägen för att minska bränsleförbrukningen, d.v.s. med hjälp av högupplösta väderdata. Vid avgång initieras en dynamisk programmering där optimering av den vertikala flygbanan och en optimal färdplan föreslås för flygbesättningen.  Bränslebesparingen som den optimala färdplanen ger är en besparingspotential som endast kan uppnås fullt ut om flygbesättningen väljer att flyga enligt den. Restriktioner från flygledningen, samt flygbesättningens vilja att följa den optimerade färdplanen kan dock påverka den uppnådda besparingen. Därav utvecklas ett verktyg för att beräkna färdens bränsleförbrukning från postflight data erhållna från Automatic Dependent Surveillance-Broadcast (ADS-B) övervakningsteknologi. En metod för att identifiera start- och slutpositionerna för kryssningssegment implementeras framgångsrikt. Två metoder för att beräkna bränslet implementeras och jämförs. Den första metoden baseras på att simulera den faktiska flygningen. Denna metod använder samma prestandamodell som för simuleringen av den operativa färdplanens resa och den optimerade resan. Den andra metoden baseras på att använda ADS-B-data för att erhålla flygplanets hastighet, som i sin tur kan användas som en parameter för att få fram flygplanets bränsleflöde vid en tidpunkt. Resultaten visar att simuleringsmetoden ger flygbanor som är rättvist jämförbara med de operativa och optimerade flygplanerna, då de använder samma modell. Men att använda ADS-B-data för att få bränsleförbrukning representerar den faktiska flygbanan mer exakt.  Dessutom implementeras en optimeringsalgoritm baserad på den inbyggda Flight Management Computer. Enligt resultaten erhåller FMC-optimeringen en tillfredsställande optimering av kryssningsfasen, jämfört med OFP-resan, men presterar sämre än den dynamiska programmeringen, vilket alltid ger en global optimal lösning.

Fuel consumption is one of the key factors in determining expenses of operating a heavy-duty vehicle. A customer may therefor request an estimate of the fuel consumption of a given vehicle. Scania uses modular design when constructing heavy-duty vehicles. The modular design allows a customer to specify which building blocks to use when constructing the vehicle, such as gear box, engine and chassis type. The many possible combinations means that the same vehicle is rarely sold twice, which can make fuel consumption measurements unfeasible. This study investigates the accuracy of machine learning algorithms in predicting fuel consumption for heavy-duty vehicles. The study is conducted at Scania. Scania has also provided the data used in the study. This study also examines the prediction power of different parameters. Performance is evaluated by reporting the prediction error on both simulated data and operational measurements. The performance of Linear regression (LR), K-nearest neighbor (KNN) and Artificial neural networks (ANN) is compared using statistical hypothesis testing. It is found that using Country as an input parameter yields a performance increase in all the algorithms. The statistical evaluation procedure finds that ANNs have the lowest prediction error compared to LR and KNN in estimating fuel consumption on both simulated and operational data. The performance of the final models is comparable to models of previous studies in both the simulated and operational estimation scenarios. / Bränsleförbrukning utgör en av nyckelfaktorerna för att avgöra hur mycket det kostar att använda tunga lastbilar. En köpare av en tung lastbil kan därmed begära en uppskattning av hur mycket bränsle ett givet fordon förbrukar. Scania använder sig av en modulär designprincip vid fordonskonstruktion, vilket ger kunden möjlighet att bestämma vilka byggnadsblock som ska utgöra ett for- don. Detta gör att det kan vara omöjligt att mäta förbrukningen av ett tidigare icke-producerat fordon. Den här studien undersöker exaktheten av maskininlärningsalgoritmer för att estimera bränsleförbrukning av tunga lastbilar. Studien genomförs vid Scania, som även tillhandahåller data. Användbarheten av olika in-parametrar undersöks. Algoritmernas prestanda utvärderas genom att rapportera det kvadrerade felvärdet uppmätt mellan det riktiga uppmätta värdet och det av algoritmen uppskattade värdet. Bränsleförbrukning estimeras för simulerad data och för uppmätta värden från fordon i bruk. Tre kategorier av algoritmer undersöks: Artificiella neurala nätverk, linjär regression och K-nearest neighbor. Jämförelsen mellan algoritmer använder statistisk hypotes-testning. Resultatet visar att parametern som beskriver vilket land fordonet registrerats i förbättrar samtliga algoritmers estimering. Den statistiska utvärderingen finner att artificiella neurala nätverk ger det lägsta felet av de tre kategorierna av algoritmer i estimering av simulerade och uppmätta värden. De slutgiltiga modellernas exakthet är jämförbar med resultat från tidigare studier.

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Formation flying of satellites describes a mission in which a set of satellites arrange their position with respect to one another. In this paper, satellite formation flying guidance and control algorithms are investigated in terms of required velocity increment Delta-v, and tracking error for a Chief/Deputy satellite system. Different control methods covering continuous and impulsive laws are implemented and tested for Low Earth Orbit (LEO). Sliding Mode, Feedback Linearization and Model Predictive Controllers are compared to an Impulsive Feedback Law which tracks the mean orbital element differences. Sliding Mode and Feedback Linearization controllers use the same dynamic model which includes Earth Oblateness perturbations. On the other hand, Model Predictive Control with Multi-Objective Cost Function is based on the Clohessy–Wiltshire equations, which do not account for any perturbation and do not cover the eccentricity of the orbit. The comparison was done for two different missions both including Earth Oblateness effects only. A relative orbit mission, which was based on the Prisma Satellite Mission and a rendezvous mission, was implemented. The reference trajectory for the controllers was generated with Yamanaka and Ankersen’s state transition matrix, while a separate method was used for the Impulsive Law. In both of the missions, it was observed that the implemented Impulsive Law outperformed in terms of Delta-v, 1.2 to 3.5 times smaller than the continuous control approaches, while the continuous controllers had a smaller tracking error, 2 to 8.3 times less, both in terms of root mean square error and maximum error in the steady state. Finally, this study shows that the tracking error and Delta-v has inversely proportional relationship. / Formationsflygning av satelliter innebär att en grupp satelliter flyger tillsammans och anpassar sina relativa lägen i förhållande till varandra. I detta examensarbete studerades regleralgoritmer för formationsflygande satelliter med fokus på bränsleförbrukning och positionsavvikelse genom ”Chief & Deputy”-metoden. Olika reglermetoder har studerats, t.ex. Sliding Mode- och Feedback Linearization-reglering för formationsflygningsfall i låg jordbana med J2-störning samt en Model Predictive-reglering för fall med relativ rörelse baserad på Clohessy-Wiltshire-ekvationerna. Vidare studerades en reglermetod baserad på impulsframdrivning. De fyra reglermetoderna implementerades på två olika rymduppdrag. Först ett uppdrag baserat på Prisma-satelliterna för två satelliter i relativ omloppsbana och sedan ett Rendezvous-uppdrag. Referensbanan för alla reglermetoder, utom för implusmetoden, har tagits fram med hjälp av Yamanakas och Ankersens tillståndsmatris. Resultaten visar att den implementerade impulsmetoden presterar bättre med avseende på bränsleförbrukning, medan de kontinuerliga reglermetoderna producerade mindre relativ positionsavvikelse, både med avseende på kvadratiskt medelvärde och maximalt värde.

The impact of air travel on the climate, along with its increasing share in CO2 emissions haveraised the demand for sustainable air travel solutions. The current aircraft technologies haveseen significant improvement throughout the years. Although, the rate at which new aircrafttechnologies are developed can not keep up with the increased demand for air travel. Hence, adifferent approach to reduce the aviation’s impact on climate can be achieved by optimizing thevertical flight path in order to reduce the fuel consumption, i.e. using dynamic programming.Upon departure, an optimization of the vertical flight path is initiated and an optimal flight planis suggested to the flight crew. The fuel saving produced by the optimal flight plan is a potential saving that can only be fullyachieved if the flight crew chose to fly according to the optimized flight path. However, restrictionsfrom the Air Traffic Control, as well as the flight crew’s willingness to follow theoptimized flight path can affect the achieved saving. Hence, a tool is developed in order tocompute trip fuel consumption from post-flight data obtained from the Automatic DependentSurveillance-Broadcast (ADS-B) surveillance technology. A method to identify the start andend positions of cruise segments is successfully implemented. Two methods of calculating thefuel are implemented and compared. The first method is based on simulating the actual flight,which uses the same performance model as for the simulation of the operational flight plantrip and optimized trip. The second method is based on utilizing the ADS-B data to obtain theaircraft speed which in return can be used as a parameter to obtain the fuel flow of the aircraft,hence the trip is not simulated. The results reveals that the simulation method produces flighttrajectories that are comparable to the operational and optimized flight plans since they use thesame model structure. However, using ADS-B data to obtain fuel consumption represents theactual flight trajectory more accurately. Furthermore, an optimization algorithm based on the on-board Flight Management Computeris implemented. According to the results, the FMC optimization offers a sufficient optimizationof the cruise phase, when compared to the OFP trip, however performs worse than the dynamicprogramming, which provides a global optimal solution / Flygresornas inverkan på klimatet, tillsammans med dess ökande andel av CO2-utsläppen, harökat kraven på hållbara flygplanslösningar. Den nuvarande flygplansteknologin har genomgåttbetydande förbättringar genom åren. Men takten för vilken ny flygplansteknik utvecklas kaninte hålla jämna steg med den ökade efterfrågan på flygresor. Däremot kan ett annat tillvägagångssättför att minska flygets påverkan på klimatet uppnås genom att optimera den vertikalaflygvägen för att minska bränsleförbrukningen, d.v.s. med hjälp av högupplösta väderdata. Vidavgång initieras en dynamisk programmering där optimering av den vertikala flygbanan och enoptimal färdplan föreslås för flygbesättningen. Bränslebesparingen som den optimala färdplanen ger är en besparingspotential som endast kanuppnås fullt ut om flygbesättningen väljer att flyga enligt den. Restriktioner från flygledningen,samt flygbesättningens vilja att följa den optimerade färdplanen kan dock påverka denuppnådda besparingen. Därav utvecklas ett verktyg för att beräkna färdens bränsleförbrukningfrån post-flight data erhållna från Automatic Dependent Surveillance-Broadcast (ADS-B) övervakningsteknologi.En metod för att identifiera start- och slutpositionerna för kryssningssegmentimplementeras framgångsrikt. Två metoder för att beräkna bränslet implementeras ochjämförs. Den första metoden baseras på att simulera den faktiska flygningen. Denna metodanvänder samma prestandamodell som för simuleringen av den operativa färdplanens resa ochden optimerade resan. Den andra metoden baseras på att använda ADS-B-data för att erhållaflygplanets hastighet, som i sin tur kan användas som en parameter för att få fram flygplanetsbränsleflöde vid en tidpunkt. Resultaten visar att simuleringsmetoden ger flygbanor somär rättvist jämförbara med de operativa och optimerade flygplanerna, då de använder sammamodell. Men att använda ADS-B-data för att få bränsleförbrukning representerar den faktiskaflygbanan mer exakt. Dessutom implementeras en optimeringsalgoritm baserad på den inbyggda Flight ManagementComputer. Enligt resultaten erhåller FMC-optimeringen en tillfredsställande optimering avkryssningsfasen, jämfört med OFP-resan, men presterar sämre än den dynamiska programmeringen,vilket alltid ger en global optimal lösning.

This paper describes efforts to optimize the parameters for a platoon identification and accommodation algorithm that minimizes vehicle emissions. The algorithm was developed and implemented in the AnyLogic framework, and was validated by comparing it to the results of prior research. A four-module flowchart was developed to analyze the traffic data and to identify platoons. The platoon end time was obtained from the simulation and used to calculate the offset of the downstream intersection. The simulation calculates vehicle emissions with the aid of the VT-Micro microscopic emission model. Optimization experiments were run to determine the relationship between platoon parameters and minimum- and maximum-emission scenarios. Optimal platoon identification parameters were found from these experiments, and the simulation was run with these parameters. The total time of all vehicles in the simulation was also found for minimum and maximum emissions scenarios. Time-space diagrams obtained from the simulations demonstrate that optimized parameters allow all cars to travel through the downstream intersection without waiting, and therefore cause a decrease in emissions by as much as 15.5%. This paper also discusses the outcome of efforts to leverage high resolution data obtained from WV-705 corridor in Morgantown, WV. The proposed model was developed for that purpose and implemented in the AnyLogic framework to simulate this particular road network with four coordinated signal-controlled intersections. The simulation was also used to calculate vehicle CO, HC, NOx emissions with the aid of the VT-Micro microscopic emission model. Offset variation was run to determine the optimal offsets for this particular road network with traffic volume, signal phase diagram and vehicle characteristics. A classifier was developed by discriminant analysis based on significant attributes of HRD. Equation of this classifier was developed to distinguish between set of timing plans that produce maximum emission from set of timing plans that produce maximum emission. Also, current work investigates the potential use of the GPS-based and similar priority systems by giving preemption through signalized intersections. Two flowcharts are developed to consider presence of emergency vehicle (EV) in the system so called EV life cycle and EV preemption (EVP). Three scenarios are implemented, namely base case scenario when no EV is involved, EV scenario when EV gets EVP only, and EV scenario when EV gets preemption by signals and right-of-way by other vehicles. Research makes an attempt to compare emission results of these scenarios to find out whether EV effects vehicle emission in the road network and what is the level of this influence if any. / Master of Science

The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is participating in the 2012-2014 EcoCAR 2: Plugging in to the Future Advanced Vehicle Technology Competition series organized by Argonne National Lab (ANL), and sponsored by General Motors Corporation (GM) and the U.S. Department of Energy (DOE). The goals of the competition are to reduce well-to-wheel (WTW) petroleum energy consumption (PEU), WTW greenhouse gas (GHG) and criteria emissions while maintaining vehicle performance, consumer acceptability and safety. Following the EcoCAR 2 Vehicle Development Process (VDP) of designing, building, and refining an advanced technology vehicle over the course of the three year competition using a 2013 Chevrolet Malibu donated by GM as a base vehicle, the selected powertrain is a Series-Parallel Plug-In Hybrid Electric Vehicle (PHEV) with P2 (between engine and transmission) and P4 (rear axle) motors, a lithium-ion battery pack, an internal combustion engine, and an automatic transmission. Development of a charge sustaining control strategy for this vehicle involves coordination of controls for each of the main powertrain components through a distributed control strategy. This distributed control strategy includes component controllers for each individual component and a single supervisory controller responsible for interpreting driver demand and determining component commands to meet the driver demand safely and efficiently. For example, the algorithm accounts for a variety of system operating points and will penalize or reward certain operating points for other conditions. These conditions include but are not limited to rewards for discharging the battery when the state of charge (SOC) is above the target value or penalties for operating points with excessive emissions. Development of diagnostics and remedial actions is an important part of controlling the powertrain safely. In order to validate the control strategy prior to in-vehicle operation, simulations are run against a plant model of the vehicle systems. This plant model can be run in both controller Software- and controller Hardware-In-the-Loop (SIL and HIL) simulations. This paper details the development of the controls for diagnostics, major selection algorithms, and execution of commands and its integration into the Series-Parallel PHEV through the supervisory controller. This paper also covers the plant model development and testing of the control algorithms using controller SIL and HIL methods. This paper details reasons for any changes to the control system, and describes improvements or tradeoffs that had to be made to the control system architecture for the vehicle to run reliably and meet its target specifications. Test results illustrate how changes to the plant model and control code properly affect operation of the control system in the actual vehicle. The VT Malibu is operational and projected to perform well at the final competition. / Master of Science