With an imminent future of fully autonomous heavy duty vehicles in offroad applications, the need for advanced control system will increase accordingly. By implementing a raster map with tiles and pixels, to which a vehicle can record slope and position data while driving, it is possible to map earth's surface. By adding a heat parameter to every pixel, i.e. the number of passings through it historically, it is possible in future visits of the same are to generate a route prediction made up by the "hottest" pixels. By fetching the slope values in the hottest pixels, it is possible to generate a slope horizon that can be utilized by control systems, e.g. when planning gear shifts in hilly offroad terrain. To mange the incrementally growing map, a memory management system was implemented. It buffers the relevant map data from the database, i.e. the vehicles closest surroundings, which is then used for route prediction and horizon generation. As the vehicle moves into other areas, new data is read from the database, and the recently passed area is written back to the database, however updated from the recent passing. The system is implemented so that it runs through another application in the telematics electrical controller unit (ECU) in a Scania vehicle. The ECU contains a GNSS module from which the vehicle fetches satellite positioning data. Slope data is fetched from a slope sensor mounted on the truck. Due to implications during testing and debugging of the resulting application developed and implemented during this thesis project, the application's performance couldn't be assessed properly. However, it is concluded that the background the application is built on is reliable, although tweaks to get the application fit for usage in offroad terrain had to be made. Mainly, the horizon length and map building techniques should not be the same as in similar applications for onroad driving.

Hybrid-electric technologies have recently been introduced into the market for heavy-duty vehicles (HDVs). However, challenging an established technology with a new and untried technology is difficult, also under the best conditions. Forecasting is a vital tool in product portfolio management, since it provides guidance on how much resources a firm should allocate on new innovative projects and products and when and where to enter the market. Therefore, this thesis forecasts the market penetration of hybrid HDVs in Europe by usage of innovation diffusion models – based on three different market scenarios assuming no, some and considerable incentives or legislative CO2 for HDVs. Hybrid-electric, hydraulic hybrid and flywheel hybrid vehicles are considered and an analogical approach is used based on sales data for radial tyres, disc brakes and anti-lock braking systems. The result from a non-linear regression analysis indicated that innovation diffusion models of mixed influence are capable of predicting future market demand, not only of hybrid HDVs, but also of other HDVs with new innovative technologies or solutions. Therefore, it was suggested that innovation diffusion modeling should be a standard tool in the strategic planning of a HDV firm’s all new innovative products. All market scenarios resulted in a rather low diffusion speed of hybrid HDVs during the first ten years, but the speed increased then rapidly during the next ten years such that 40-50 percent of the HDV market was penetrated in 2030. In the most hybrid-friendly scenario, the market was nearly fully penetrated after 50 years since the first introduction in 2010, while in the least hybrid-friendly scenario additional ten years was needed to fully penetrate the HDV market. The forecasts may be affected by possible pre-diffusion, the emergence of a dominant design or the diffusion acceleration effect. One of the major challenges of using innovation diffusion models for sales forecasting of hybrid HDVs, was to find appropriate and sufficient analogous sales data. Therefore, Thomas (1985) analogous approach was further developed to be more focused on finding analogous sales data from internal, external or public sources.

For this project, a Software-In-the-Loop (SIL) simulation tool is used at Scania (“VTAB” – Virtual Truck and Bus), which simulates the submodels of the mechanical vehicle components together with the real control units. The simulation tool contains the following submodels: Engine model, Drivetrain model, Drive cycle model, Restbus model, and Driver model. The simulated human driver submodel in the restbus model outputs two pedal control signals to the control unit, namely the gas and brake pedals. With these two pedal signals, the control unit decides the modes of mechanical vehicle components. This driver model needs to be reworked to obtain a better velocity following performance. Two controllers, fuzzy PI anti-windup and backward calculation, are implemented in the driver model and compared by the velocity tracking accuracy and the pedal switching frequency. In the comparison and analysis section, two different cycles and two weights of payload are simulated. The simulation results demonstrate that both controllers can improve the driver model’s velocity tracing accuracy. Further, the fuzzy PI anti-windup controller is better when considering pedal signals fluctuation frequency and implementation complexity. / För detta projekt används ett simuleringsverktyg Software-In-the-Loop (SIL) på Scania (“VTAB” - Virtual Truck and Bus), vilket simulerar submodellerna för de mekaniska fordonskomponenterna tillsammans med de verkliga styrenheterna. Simuleringsverktyget innehåller följande submodeller: Motormodell, Drivmotormodell, Drivcykelmodell, Restbusmodell och Drivermodell. Den simulerade submodellen för mänsklig förare i restbussmodellen kommer att sända två pedalsstyrsignaler till styrenheten, nämligen gas och broms. Med dessa två pedalsignaler kan styrenheten avgöra lägen av mekaniska fordonskomponenter. Denna drivrutinmodell måste omarbetas för att få en bättre hastighetsspårnings presentationsförmåga. Två styrenheter, fuzzy PI anti-windup och bakåtberäkning, implementeras i förarmodell och jämförs respektive med hastighetsspårningsnoggrannhet och pedalväxelfrekvens. I jämförelseoch analysavsnittet simuleras två olika cyklar och två nyttolast. Simuleringsresultaten visar att båda kontrollerna kan förbättra förarmodellens hastighetsspårningskapacitet. Vidare är fuzzy PI-anti-windup-kontroller bättre när man tar hänsyn till pedalsignalernas fluktueringsfrekvens och implementeringskomplexitet

Within the most pollutants industries, the energy sector is the most significant contributor to climate change, representing two-thirds of the total Greenhouse Gas (GHG) emissions. One of the main responsible for these emissions is transportation, which accounts for 26% of the world’s energy consumption, with crude oil-derived products providing more than 90% of this energy. In Europe, the transport sector is the only sector that has experienced an upward trend of GHG emissions between 1990 and 2017, opposite to all others, such as agriculture, residential, or industry. To cut these growing GHG emissions, transport electrification has been presented as a potential and promising solution for decarbonization thanks to the no tail-pipe emissions and the possibility of using renewable energy to power them. One particularly interesting segment of the transport sector is Heavy Duty Trucks (HDTs) used for freight transport. HDTs are the backbone of the Swedish economy and competitiveness since they represent 45% of its total goods transportation. However, the Swedish transmission grid needs to evolve parallelly to cope with the increase in electricity demand and withstand the Charging Infrastructure (CI) necessary for the electrification of HDTs. Oskarshamn is a Swedish municipality that presents a high potential for electrification of its HDTs, which are currently operated with diesel. Therefore, the objective of this Master Thesis is to study the implementation of Electric Heavy Vehicles (EHVs) CI in Oskarshamn by collaborating with local interested stakeholders. The study is conducted through an analysis of the current status of EHV technologies, as well as CI possibilities, which, together with the information provided by truck operators from Oskarshamn, allows to perform a techno-economic assessment of the solution and analyze the business model of its operation. A virtual model is created with Python to simulate the actual operating conditions, which uses all the information gathered and optimizes the CI design while fulfilling all its transport requirements. Additionally, the study seeks to identify potential areas for shared ownership of the CI to increase the project's feasibility. This project’s findings demonstrate that electrification of freight transportation brings financial and sustainable benefits for truck operators while presenting a diverse range of options to meet their specific transportation requirements. Furthermore, by effectively negotiating ownership terms and electricity tariffs for CI, there is potential to further enhance business profitability. / Inom de mest förorenande industrierna är energisektorn den mest betydande bidragsgivaren till klimatförändringarna och står för två tredjedelar av de totala utsläppen av växthusgaser (GHG). En av de huvudsakliga ansvariga för dessa utsläpp är transportsektorn, som står för 26% av världens energiförbrukning, där produkter som härstammar från råolja utgör över 90% av denna energi. I Europa är transportsektorn den enda sektorn som har upplevt en ökande trend av GHG-utsläppen mellan 1990 och 2017, till skillnad från alla andra sektorer. Därför är elektrifiering av transporten en potentiell och lovande lösning för avkolning, tack vare frånvaron av avgasutsläpp och möjligheten att använda förnybar energi för att driva fordonen. En särskilt intressant del av transportsektorn är tunga lastbilar (HDTs) som används för godstransport. HDTs utgör ryggraden i den svenska ekonomin och konkurrenskraften eftersom de står för 45% av den totala godstransporten. Dock behöver det svenska transmissionsnätet utvecklas parallellt för att klara av ökningen av elförbrukningen och klara av laddinfrastrukturen (CI) som krävs för elektrifieringen av HDTs. Oskarshamn är en svensk kommun som har stor potential för elektrifiering av sina HDTs, som för närvarande drivs med diesel. Därför är målet med detta examensarbete att studera implementeringen av laddinfrastruktur för eldrivna tunga fordon (EHVs) i Oskarshamn genom samarbete med lokala intressenter. Studien genomförs genom en analys av den aktuella statusen för EHVs-teknologier, samt CI-möjligheter, vilket, tillsammans med informationen som tillhandahålls av lastbilsoperatörer från Oskarshamn, möjliggör en teknisk-ekonomisk bedömning av lösningen och analyserar affärsmodellen för dess drift. En virtuell modell skapas med hjälp av Python för att simulera de faktiska driftsförhållandena, vilket utnyttjar all insamlad information och optimerar designen av CI samtidigt som alla transportkrav uppfylls. Dessutom syftar studien till att identifiera potentiella områden för delägarskap av CI för att öka projektets genomförbarhet. Denna projekts resultat visar att elektrifiering av godstransport ger ekonomiska och hållbara fördelar för lastbilsoperatörer samtidigt som det presenterar ett brett utbud av alternativ för att möta deras specifika transportkrav. Dessutom finns det potential att ytterligare förbättra affärs lönsamheten genom effektivt förhandla om ägandevillkor och eltariffer för CI.

The demand for road freight transport continues to grow with the growing economy, resulting in increased fossil fuel consumption and emissions. At the same time, the fossil fuel use needs to decrease substantially to counteract the ongoing global warming. One way to reduce fuel consumption is to utilize emerging intelligent transport system (ITS) technologies and introduce heavy-duty vehicle (HDV) platooning, i.e. HDVs driving with small inter-vehicle gaps enabled by the use of sensors and controllers. It is of importance for transport authorities and industries to investigate the effects of introducing HDV platooning. Previous studies have investigated the potential benefits, but the effects in real traffic, both for the platoons and for the surrounding vehicles, have barely been explored. To further utilize ITS and optimize the platoons, information about the traffic situation ahead can be used to optimize the vehicle trajectories for the platoons. Paper I presents a dynamic programming-based optimal speed control including information of the traffic situation ahead. The optimal control is applied to HDV platoons in a deceleration case and the potential fuel consumption reduction is evaluated by a microscopic traffic simulation study with HDV platoons driving in real traffic conditions. The effects for the surrounding traffic are also analysed. Paper II and Paper III present a simulation platform to assess the effects of HDV platooning in real traffic conditions. Through simulation studies, the potential fuel consumption reduction by adopting HDV platooning on a real highway stretch is evaluated, and the effects for the other vehicles in the network are investigated. / Efterfrågan på godstransporter på väg fortsätter att öka i takt med den växande ekonomin, vilket resulterar i ökad förbrukning av fossila bränslen och ökade utsläpp. Samtidigt behöver användandet av fossila bränslen minska för att motverka den pågående globala uppvärmningen. Ett sätt för att minska bränsleförbrukningen är att utnyttja den teknik kring intelligenta transportsystem som är under utveckling och introducera lastbilskonvojer, det vill säga lastbilar som använder sensorer och regulatorer för att kunna köra med korta avstånd mellan sig. För transportföretag och -myndigheter är det viktigt att undersöka effekterna av att införa lastbilskonvojkörning. Tidigare studier har undersökt de möjliga fördelarna, men effekterna vid körning i trafik, både för konvojerna och för omgivande fordon, är outforskade. För att ytterligare utnyttja intelligenta transportsystem och optimera konvojerna kan information om trafiksituationen längre fram på vägen användas för att optimera konvojernas körning. Artikel I presenterar en optimal hastighetsregulator baserad på dynamisk programmering och som inkluderar information om trafiksituationen längre fram. Den optimala regulatorn appliceras på lastbilskonvojer under ett inbromsningsscenario och den potentiella minskningen i bränsleförbrukning utvärderas genom en mikroskopisk trafiksimuleringsstudie där lastbilskonvojerna kör i verkliga trafikförhållanden. Effekterna för omgivande fordon är också analyserade.Artikel II och artikel III presenterar en simuleringsplattform för att utvärdera effekterna av lastbilskonvojkörning i verkliga trafikförhållanden. Genom simuleringsstudier analyseras den potentiella bränsleförbrukningsminskningen då lastbilskonvojer körs på en verklig motorvägssträcka och effekterna för de övriga fordonen på vägen undersöks. / <p>QC 20180516</p>

The interest in autonomous vehicles has never been higher and there are several components that need to function for a vehicle to be fully autonomous; one of which is the ability to perform a parking at the end of a mission. The objective of this thesis work is to develop and implement an automatic parking system (APS) for a heavy-duty vehicle (HDV). A delimitation in this thesis work is that the parking lot has a known structure and the HDV is a truck without any trailer and access to more computational power and sensors than today's commercial trucks. An automatic system for searching the parking lot has been developed which updates an occupancy grid map (OGM) based on measurements from GPS and LIDAR sensors mounted on the truck. Based on the OGM and the known structure of the parking lot, the state of the parking spots is determined and a path can be computed between the current and desired position. Based on a kinematic model of the HDV, a gain-scheduled linear quadratic (LQ) controller with feedforward action is developed. The controller's objective is to stabilize the lateral error dynamics of the system around a precomputed path. The LQ controller explicitly takes into account that there exist an input delay in the system. Due to minor complications with the precomputed path the LQ controller causes the steering wheel turn too rapidly which makes the backup driver nervous. To limit these rapid changes of the steering wheel a controller based on model predictive control (MPC) is developed with the goal of making the steering wheel behave more human-like. A constraint for maximum allowed changes of the controller output is added to the MPC formulation as well as physical restrictions and the resulting MPC controller is smoother and more human-like, but due to computational limitations the controller turns out less effective than desired. Development and testing of the two controllers are evaluated in three different environments of varying complexity; the simplest simulation environment contains a basic vehicle model and serves as a proof of concept environment, the second simulation environment uses a more realistic vehicle model and finally the controllers are evaluated on a full-scale HDV. Finally, system tests of the APS are performed and the HDV successfully parks with the LQ controller as well as the MPC controller. The concept of a self-parking HDV has been demonstrated even though more tuning and development needs to be done before the proposed APS can be used in a commercial HDV.

This thesis presents a predictive energy management controller for long-haul hybrid trucks. In a receding horizon control framework, the vehicle speed reference, battery energy reference, and engine on/off decision are optimized over a prediction horizon. A mixed-integer quadratic program (MIQP) is formulated by performing modelling approximations and by including the binary engine on/off decision in the optimal control problem. The branch-and-bound algorithm is applied to solve this problem. Simulation results show fuel consumption reductions between 10-15%, depending on driving cycle, compared to a conventional truck. The hybrid truck without the predictive control saves significantly less. Fuel consumption is reduced by 3-8% in this case. A sensitivity analysis studies the effects on branch-and-bound iterations and fuel consumption when varying parameters related to the binary engine on/off decision. In addition, it is shown that the control strategy can maintain a safe time gap to a leading vehicle. Also, the introduction of the battery temperature state makes it possible to approximately model the dynamic battery power limitations over the prediction horizon. The main contributions of the thesis are the MIQP control problem formulation, the strategy to solve this with the branch-and-bound method, and the sensitivity analysis.

More efficiency heavy-duty vehicles are developed with higher range, updated electronic and mechanical parts. The fuel efficiency and pollution of carbon dioxide need to be lower to achieve new EU regulations. The global population increases with an increased number of heavy-duty vehicles. This, in turn, increases the emission. By taking the electrical and mechanical parts to the next step, the global emission problems can be massively reduced. Electrical machines are the next step towards a cleaner future. The main goal of this study to investigate the electrical machine’s insulation system. Thermo-mechanical stresses due to thermal cycling affect the electrical machines and its sub-components. By using a FEM application with simplified models of the electrical machine, results are obtained and discussed. Specifically, if 2D-models are sufficient enough to represent a 3D-model. How good different 2D-models can represent the 3D-model is compared and discussed in this study. A physical experimental analysis is done to verify and calibrate the FE-models. Which one of the less frequent higher amplitude or more frequent, lower amplitude thermal cycling affects the insulation system most is determined. The simulations could be done with either, coupled-temperature displacement analysis or sequentially coupled analysis. Coupled-temperature displacement is the fastest method to use in the simulation models. A 3D-model is the best way to describe an object and is therefore implemented. Two additional 2D-models are developed for faster computation and to investigate if the models can represent the three-dimensional geometry. All the models have specific boundary conditions to make the models more simplified. Sensitivity studies have been done to determine which parameter affects the induced thermo-mechanical stresses the most. A physical experimental setup is also implemented to validate and calibrate the simulation model. The result of the 3D-model is most accurate when simulating a three-dimensional object. Simulation results have shown that epoxy, one of the main components in the insulation system, is most critical in terms of reaching breakdown first, followed by paper insulation and copper coating. This is a typical result of all three simulation models. Whereas it is concluded that some 2D-models can present the 3D-model, others can’t. The dependent factor is the different cross-section of the electrical machine. The physical experiment shows similar results between simulation in terms of strain at a lower temperature, and the deviation gets larger as the temperature increases. The 3D-model is the model that has the best representation of a real electrical machine as it accounts for all the normal and shear stress components in all directions, but also because it has better boundary conditions compared to the 2D-models. The 2D-model in XY-plane has shown similar results to the 3D-model. One of the main insulation system components, epoxy, is exposed to the highest stresses compared to its yield and ultimate strength, followed by the paper insulation and copper coating. The sensitivity study has concluded that the axial length of the stator does not affect the stress amplitudes. The most critical parameter that affects the thermo-mechanical stresses is the temperature amplitude, the materials CTE and the thickness of the jointed layer. All maximum stress amplitudes of all the components are located at the free end. / Mer effektiva tunga fordon utvecklas med högre räckvidd, uppdaterade elektroniska och mekaniska delar. Bränsleeffektiviteten och föroreningen av koldioxid måste vara lägre för att uppnå nya EU-förordningar. Antalet tunga fordon ökar i takt med att den globala befolkningen ökar, detta leder i sin tur till ökad utsläpp av bland annat koldioxid. Genom att ta de elektriska och mekaniska delarna till nästa steg kan de globala utsläppsproblemen minskas massivt. Elektriska maskiner för framdrivning är nästa steg mot en renare framtid. Studiens huvudmål för att undersöka den elektriska maskinens isoleringssystem. Termomekaniska påfrestningar på grund av termisk cykling påverkar de elektriska maskinerna och dess delkomponenter. Genom att använda en FEM-applikation med förenklade modeller av den elektriska maskinen erhålls och diskuteras resultat. Specifikt om 2D-modeller är tillräckliga för att representera en 3D-modell. Hur tillräckligt de olika 2D-modeller kan representera 3D-modellen jämförs och diskuteras i denna studie. Ett fysiskt experiment utförs för att validera och kalibrera FEA-modellerna. Vilken av de mindre frekventa cykler med högre amplitud eller mer frekventa cyckler med lägre amplitud påverkar isoleringssystemet mest har undersökts. Simuleringarna kan göras med antingen, temperatur kopplad förskjutnings analys eller sekventiellt kopplad analys. Temperatur kopplad kopplad förskjutning är den snabbaste metoden att använda i simuleringsmodellerna. En 3D-modell är det bästa sättet att beskriva ett objekt och har därför implementerats. Ytterligare två, 2Dmodeller är framtagna i FEM-miljö för snabbare beräkning och för att undersöka om 2D-modellerna kan representera den tredimensionella geometrin. Samtliga tre modeller har specifika randvillkor för att förenkla modellerna. Känslighetsstudier görs för att bestämma vilken parameter som påverkar de inducerade termomekaniska spänningarna mest. Ett fysiskt experiment har utförsts för att validera och kalibrera simuleringsmodellerna. Resultatet visar att 3D-modellen representerar ett tre dimensonellt objekt bäst. Simuleringsresultat har visat att epoxy, som är en av huvudkomponenterna i isoleringssystemet, är mest kritisk när det gäller att först nå brott- och sträckgräns, följt av pappersisolering och koppar beläggningen. Detta är ett typiskt resultat av alla tre simuleringsmodeller. Slutsatsen visar att vissa 2D-modeller kan presentera 3D-modellen, andra kan inte. Den beroende faktorn beror på ur vilket tvärsnitt man tittar på den elektriska maskinen. Det fysiska experimentet visar liknande resultat jämfört med simuleringen när det gäller belastning vid en lägre temperatur, och avvikelsen blir större när temperaturen ökar. 3D-modellen, är den modell som har den bästa representationen av en riktig elektrisk maskin eftersom den inkluderar normal- och skjuvspänningskomponenter i alla riktningar. Anledningen är att den har bättre randvillkor jämfört med 2Dmodellerna. 2D-modellen i XY-planet har visat liknande resultat som 3D-modellen. En av huvudkomponenterna i isoleringssystemet, epoxy, utsätts för de högsta spänningarna jämfört med dess sträck- och den brottgräns, följt av pappersisolering och koppar beläggning. Känslighetsstudien har kommit fram till att statorns axiella längd inte påverkar spänningsamplituderna. Den mest kritiska parametern som påverkar de termomekaniska spänningarna är temperatur amplituden, materialens CTE och tjockleken på det skarvade skiktet. Alla maximala spänningsamplituder för samtliga tre komponenter är belägna i den fria änden.

<p>The weight of a heavy duty vehicle plays an important role when dealing with different control systems. Examples of control units in a truck that need this parameter are the ones used to control the brakes, the engine and the gearbox. An accurate estimation of the weight leads not only to a more fuel efficient and safer transport, but also assures the driver that current law limits are not exceeded. The weight can be estimated with pretty good accuracy if the truck is equipped with air suspension. In trucks that lack this type of suspension other methods are used to estimate the weight. At present these methods are inaccurate. In this thesis a new method where the weight is to be estimated through frequency analysis of the truck's driveline is developed and evaluated.</p>

The weight of a heavy duty vehicle plays an important role when dealing with different control systems. Examples of control units in a truck that need this parameter are the ones used to control the brakes, the engine and the gearbox. An accurate estimation of the weight leads not only to a more fuel efficient and safer transport, but also assures the driver that current law limits are not exceeded. The weight can be estimated with pretty good accuracy if the truck is equipped with air suspension. In trucks that lack this type of suspension other methods are used to estimate the weight. At present these methods are inaccurate. In this thesis a new method where the weight is to be estimated through frequency analysis of the truck's driveline is developed and evaluated.