The automotive and heavy-duty trucking industries are heading towards research and development of alternative powertrain solutions to meet the United Nations sustainability goals and cleaner solutions to aid climate change actions. This thesis project aligns with the vision of finding greener and sustainable modes of transport in the heavy long haulage trucking industry. This project aims to find and develop a method for creating drive cycles, getting the vehicular power requirements to drive on these selected routes and finally calculating the TCO of a vehicle. The scripts for these mentioned steps are developed in MATLAB. The approach used in this work could help both the vehicle manufacturer and the vehicle operator to predict or cater to upcoming customer demand on, in our case, routes pan EU, to receive information about energy, power and vehicular configuration needed to fulfil the mission, and also, optimize the powertrain configuration in collaboration with a parallel thesis work done here at Scania, and finally calculate a somewhat simplified TCO of the vehicle.  In this work, two different driving conditions has been used; summer or winter, and two different payload conditions, as well as two types of vehicle powertrains; FCEV and BEV. Finally, a comparison regarding TCO for FCEV and BEV has been done. / Fordonsindustrin, inklusive den kommersiella lastbilsindustrin, driver utvecklingen av alternativa drivlinor för att kunna uppfylla FN:s hållbarhetsmål kring miljövänligare lösningar, nödvändiga för att stödja det globala klimatarbetet. Detta examensarbete utgår från visionen att hitta miljövänligare fordonstyper inom den kommersiella lastbilssektorn. Detta projekt siktar på att utveckla och använda metoder för att kunna ta fram relevanta körcykler, fastställa nödvändig framdrivningseffekt för att fordonen ska kunna köra på utvalda rutter, samt att beräkna total ägandekostnad (TCO) för fordonsoperatören.  Skripten för dessa nämnda steg har utvecklats i MATLAB inom projektet. Tillvägagångssättet som har använts i detta arbete kan hjälpa både fordonstillverkare och fordonsoperatörer att förutspå framtida krav. I vårt fall har information om nödvändig energimängd, effekt och komponentkonfiguration, inklusive drivlineoptimering, tagits fram för rutter inom EU, tillsammans med ett parallellt examensarbete som också utförts på Scania. Slutligen beräknades den totala ägandekostnaden (TCO) för kunden.  I detta arbete har två olika användarfall analyserats; sommar och vinter, för två olika nyttolaster, samt två typer av drivlinor; FCEV och BEV. Slutligen, har en jämförelse gjorts gällande TCO för FCEV och BEV.

Fuel Cell Hybrid Electric vehicles are hybrid vehicles that consist of both fuel cells and batteries as energy conversion systems. The Energy Management System plays an important role in the operation of the fuel cell hybrid system, as it helps in reducing the hydrogen consumption of the system. This study investigates an optimal control algorithm with an aim to reduce the hydrogen consumption of the fuel cell system for five different drive cycles operating in Europe. Model Predictive Control(MPC) is used to solve the optimal control problem, by formalizing a look ahead controller, utilizing its receding horizon approach. The optimal controller analysis is compared with a conventional rule-based controller, by analysing the hybrid system over various battery and fuel cell sizes, on the basis of the overall hydrogen consumption. Firstly, a simplified system model is developed, by modelling the fuel cell system with respect to the efficiency curve of the hydrogen power and fuel cell power. The battery system model with its State of Charge(SOC) is coupled with the fuel cell model to form an objective function satisfying the power demand from the drive cycles. The MPC controller and the rule-based controller are implemented in MATLAB and the powersplit analysis is simulated for all five routes. The results show that the energy management system with the MPC controller optimizes the powertrain configuration efficiently, with preparing for the uphill or downhill, such that the battery SOC stays in its limits and the fuel cell operates in the most efficient range. This ensures operating over different types of drive cycles with the most efficient battery and fuel cell size, hence concluding with the MPC controller outperforming the rule-based one. / Fuel Cell Hybrid Electric Vehicle (FCHEV) är hybridfordon som består av både bränsleceller och batterier som energiomvandlingssystem. Energy ManagementSystem (EMS) spelar en viktig roll i driften av bränslecellshybridsystemet, eftersom det hjälper till att minska systemets vätgasförbrukning. Denna studie undersöker en optimal styralgoritm framtagen i syfte att minska syfte att minska vätgasförbrukningen i bränslecellssystemet. Algoritmen testas på fem olika körcykler, baserade på verkliga Europeiska vägsträckor. Model Predictive Controller (MPC) används för att lösa det optimala styrproblemet, genom att formalisera en framåtblickskontroller med hjälp av dess vikande horisont. Den optimala kontroller jämförs med en konventionell regelbaserad kontroller, genom att analysera hybridsystemet över olika batteri- och bränslecellstorlekar, baserat på den totala väteförbrukningen. Först utvecklas en förenklad systemmodell, som modellerar bränslecellssystemet med avseende på effektivitetskurvan för vätgaskraften och bränslecellseffekten. Batterisystemmodellen med dess State of Charge (SOC) är kopplad till bränslecellsmodellen för att bilda en målfunktion som tillfredsställer kraftbehovet från drivcyklerna. MPC-styrningen och den regelbaserade styrningen är implementerade i matlab och effektdelningsanalysen simuleras för alla fem rutterna. Resultaten visar att energihanteringssystemet medMPC-styrningen optimerar drivlinans konfiguration effektivt, med förberedelser för uppförsbacke eller nedförsbacke, så att batteriets SOC håller sig inom sina gränser och bränslecellen arbetar i mest optimala räckvidden. Detta säkerställer drift över olika typer av körcykler med den mest effektiva batteri- och bränslecellsstorleken, och avslutar därför med att MPC-styrenheten överträffar den regelbaserade.

Lithium-ion (Li-Ion) batteries are widely used in various applications and are viable for automotive applications. The effective management of Li-Ion batteries in battery electric vehicles (BEV) plays a crucial role in performance and range. One can achieve good performance and range by using efficient battery models in battery management systems (BMS). Hence, these battery models play an essential part in the development process of battery electric vehicles. Physics-based battery models are used for design purposes, control, or to predict battery behaviour, and these require much information about materials and reaction and mass transport properties. Model parameterization, i.e., obtaining model parameters from different experimental sets (by fitting the model to experimental data sets), can be challenging depending on model complexity and the type and quality of experimental data. Based on the idea of parameter sensitivity, certain current/voltage data sets could be chosen that theoretically has a more considerable sensitivity for a given model parameter that is of interest to extract. In this thesis work, different methods for extracting model parameters for a Nickel-Manganese-Cobalt (NMC) battery composite electrode are experimentally tested and compared. Specifically, model parameterization using \emph{optimal experiments} based on performed parameter sensitivity analysis has been benchmarked against a 1C discharge test and low rate pulse tests. The different parameter sets obtained have then been validated on a drive cycle and 2C pulse tests. Comparing the methods show some promising results for the optimal experiment design (OED) method, but consideration regarding the state of charge (SOC) dependencies, the number of parameters has to be further evaluated. / Litiumjonbatterier (Li-jon) används i olika applikationer och är ett bra alternativ förfordonsapplikationer. Den effektiva hanteringen av litiumjonbatterier i elbilar har en viktigroll för fordonens prestanda och räckvidd. Man kan nå bra prestanda och räckviddgenom att använda bra batterimodeller i batteriets övervakningssystem (BMS). Därförspelar dessa batterimodeller en viktig roll i utvecklingen av elbilar. Fysikbaseradebatterimodeller används för design, reglering eller för att prediktera beteendet hos batteriet,vilket kräver mycket information om material samt dess reaktion och andra beskaffenheter.Modellparametrisering, dvs. att införskaffa modellparametrar från olika experiment (genom attanpassa modell till experimentella data) kan vara utmanande beroende på modellkomplexitetoch typen samt kvalitén på experimentell data. Baserat på idén om parametersensitivitet kan data om ström och spänning väljas så att de teoretiskt har mer sensitivitet för engiven modellparameter som är av intresse att extrahera. I detta examensarbete testas ochjämförs olika metoder för att extrahera modellparametrar för en Nickelmangankobolt (NMC)batterielektrod. Mer specifikt, modellparametrisering genom optimala experiment baseradepå genomförd parametersesitivitetsanalys jämförts med 1C urladdningstest och låg nivåpulstest. Jämförande av metoderna visar goda resultat för OED metoden men flera parametrarmåste fortsatt utvärderas gällande laddningstatusberoenden (SOC).

The transition in the transport sector by the integration of battery electric vehicles (BEVs) brings a new challenge for the system operators to ensure the balance between supply and demand. The installation of new EV charges poses a surge in electricity demand in the coming years which jeopardizes the grid reliability and stability. With the new EV policies in place, Sweden will have a huge growth of BEVs and the associated charging infrastructures. The challenges faced by the electricity transmission and distribution will depend on the type and smart capability of the infrastructure. Therefore, research is conducted to analyze the impacts of the mix of public and private residential EV charging and how smart charging can help in mitigating the impacts. This thesis studies the impact of the mix of private residential and public EV chargers on the power network of Hammarby Sjöstad, a neighborhood of Stockholm. Four substations out of 20 corresponding to the areas with the highest proportion in the residential and commercial sectors in the network were chosen for the study and power flow analysis was carried out to analyze the impacts in the year 2025. EV chargers were categorized into public and private residential chargers. The public chargers had rated power of 22 kW each while residential chargers were rated at 3.68 kW each. EVs can behave as energy vectors, and it is possible to optimize their charging as a part of demand-side management which includes peak shaving or shifting. Optimizing EV charging was treated as a mixed integer linear programming (MILP) problem to schedule EV charging for both reducing losses and the cost of electricity import from the grid. Two optimization strategies were investigated to analyze their potential to reduce the peaks due to uncontrolled charging. Renewable energy generation from solar PVs integrated with EV chargers reduces the import of electricity from the grid during the day which not only reduced the losses but also the cost of importing electricity from the grid. The effect of intermittency of solar PV generation was reduced by implementing BESS. At low price periods, the BESS was charged using the excess PV power and at higher price periods, the BESS was discharged. Three scenarios were developed, where the Reference scenario refers to the base case without PV and BESS, With PV scenario considered only PV generation while With PVBESS scenario considered the implementation of BESS with PV. Three test cases were simulated for each of the scenarios, and it was found that by the implementation of smart charging, the losses in the network reduce by 35.5% and it also significantly reduced the losses in all the other scenarios. Implementation of smart charging reduced the cost of electricity import from the grid by 4.3%. The integration of PV generation led to a 7% further reduction in the losses and cost of electricity import as compared to the Reference scenario. The integration of BESS increased the losses in the network, but it also enhanced the self-consumption of PV power. The implementation of smart charging not only reduces the losses and costs of import but will lead to savings in grid reinforcement costs. / Övergången inom transportsektorn genom integrering av batteri -elektriska fordon (BEV) medför en ny utmaning för systemoperatörerna att säkerställa balansen mellan utbud och efterfrågan. Installationen av nya elavgifter innebär en kraftig ökning av elbehovet under de kommande åren, vilket äventyrar nätets tillförlitlighet och stabilitet. Med den nya EV -politiken på plats kommer Sverige att ha en enorm tillväxt av BEV och tillhörande ladd infrastrukturer. Utmaningarna för elöverföring och distribution beror på infrastrukturens typ och smarta kapacitet. Därför forskas för att analysera effekterna av blandningen av offentliga och privata EV -laddningar för bostäder och hur smart laddning kan hjälpa till att mildra effekterna. Denna avhandling studerar effekten av blandningen av privata bostäder och offentliga EV -laddare på kraftnätet i Hammarby Sjöstad, en stadsdel i Stockholm. Fyra transformatorstationer av 20 motsvarande de områden med den högsta andelen inom bostads- och kommersiella sektorer i nätet valdes ut för undersökningen och effektflödesanalys utfördes för att analysera effekterna år 2025. EV -laddare kategoriserades offentligt och privata bostadsladdare. De offentliga laddarna hade en nominell effekt på 22 kW vardera medan bostadsladdare var 3,68 kW vardera. Elbilar kan bete sig som energivektorer, och det är möjligt att optimera laddningen som en del av hanteringen på efterfrågesidan som inkluderar topprakning eller växling. Optimering av EV -laddning behandlades som ett blandat heltal linjärt programmeringsproblem (MILP) för att schemalägga EV -laddning för både minskning av förluster och kostnader för elimport från nätet. Två optimeringsstrategier undersöktes för att analysera deras potential att minska topparna på grund av okontrollerad laddning. Förnybar energiproduktion från solcellsanläggningar integrerade med EV -laddare minskar importen av el från nätet under dagen vilket inte bara minskade förlusterna utan också kostnaderna för att importera el från nätet. Effekten av intermittency av solcellsgenerering genererades genom att implementera BESS. Vid lågprisperioder debiterades BESS med överskott av PV -effekt och vid högre prisperioder laddades BESS ur. Tre scenarier utvecklades, där referensscenariot hänvisar till basfallet utan PV och BESS, med PV -scenario endast betraktat PV -generering medan With PVBESS -scenario övervägde implementeringen av BESS med PV. Tre testfall simulerades för vart och ett av scenarierna, och det visade sig att genom implementering av smart laddning minskar förlusterna i nätverket med 35,5% och det minskade också avsevärt i alla andra scenarier. Genomförandet av smart laddning minskade kostnaden för elimport från nätet med 4,3%. Integrationen av PV -produktion ledde till en ytterligare minskning av förlusterna och kostnaderna för elimport med 7% jämfört med referensscenariot. Integrationen av BESS ökade förlusterna i nätet, men det förbättrade också självförbrukningen av PV-kraft. Genomförandet av smart laddning minskar inte bara förluster och kostnader vid import utan leder till besparingar i nätförstärkningskostnader.

To reduce the emissions from the transport sector, the electric vehicle (EV) is a promising alternative to the internal combustion engine vehicle (ICEV). An important aspect of implementing new transport systems in terms of EVs is the charging strategy, as many energy sources with different limitations can be utilized. Although various studies have investigated charging strategies for electric cars, there is a lack of optimized charging strategies for electric boats with specific considerations for these cases. In Colombia, the river transport sector plays an important role in areas with lack of access to other transport alternatives. This study presents an optimization of the charging strategy for an electric boat that is planned to traffic the Magdalena River in the region of Magangué, Colombia. The objective of the optimization model is to minimize the electricity bill while maintaining a desired transport service. The study considers solar photovoltaics (PV), the electric grid and battery storage for charging, and compares different battery sizes in a scenario analysis. Furthermore, the impact of the instability of the grid is included in terms of a sensitivity analysis of grid blackouts, together with varying battery investment costs. The results show that PV is a recommended investment as it lowers the charging cost and gives positive results in terms of economic feasibility. To further increase the economic feasibility, lower the charging costs and improve the reliability of the system, it is suggested to invest in energy storage. The techno-economic feasibility of storage is heavily affected by battery investment costs and number of grid blackouts affecting the boat charging. If the investment cost is low and the number of blackouts is high, a large storage is a suggested solution. / För att minska utsläppen från transportsektorn är elfordon (EV) ett lovande alternativ till förbränningsmotorfordon (ICEV). En viktig aspekt vid implementering av nya transportsystem för EV:s är val av laddningsstrategi, eftersom många energikällor med olika begränsningar kan användas. Även om flertalet studier har undersökt laddningsstrategier för elbilar, saknas optimerade laddningsstrategier för elbåtar och som beaktar de specifika förhållandena för dessa fall. I Colombia spelar flodtransportsektorn en viktig roll i områden med brist på tillgång till andra transportalternativ. Denna studie presenterar en optimering av laddningsstrategin för en elbåt som är planerad att trafikera floden Magdalena i regionen Magangué, Colombia. Syftet med optimeringsmodellen är att minimera elräkningen samtidigt som en önskad transporttjänst bibehålls. Studien omfattar solceller (PV), elnätet och batterilagring för laddning, och jämför olika batteristorlekar i en scenarioanalys. Vidare inkluderas effekterna av elnätets instabilitet genom en känslighetsanalys av strömavbrott, tillsammans med varierande kostnader för batteriinvesteringar. Resultaten visar att PV är en rekommenderad investering eftersom den sänker laddningskostnaden och ger positiva resultat när det gäller ekonomisk lönsamhet. För att ytterligare öka den ekonomiska lönsamheten, sänka laddningskostnaderna och förbättra systemets tillförlitlighet föreslås det att investera i energilagring. Den teknisk-ekonomiska genomförbarheten för lagring påverkas starkt av kostnader för batteriinvesteringar och antalet strömavbrott som påverkar båtladdningen. Om investeringskostnaden är låg och antalet strömavbrott är högt är energilagring med stor kapacitet en föreslagen lösning.

Functional and cost effective systems for the full electrification of a bus network are areas of intense research and development. The electrification can be accomplished using different technological solutions, for example using opportunity charging or using an electric road system – ERS. Both opportunity charging and ERS have the potential to be integrated into already existing bus lines. With opportunity charging, the regular dwell time at the end stops is used for the bus to recharge its batteries and with an ERS the bus can charge dynamically along the road. The purpose of this report is to analyze how the existing Alfa- and Beta line at Stockholm Arlanda Airport, in a functional and cost effective way, can be electrified using either opportunity charging or an ERS. The tradeoff between required charging power, battery capacity and the necessity to change the existing running schedule is explained in detail. In addition, the impact on the electrical grid is analyzed based on different load profiles of different charging stations using different power levels. The analysis is based on real data from the Alfa – and Beta line with its existing buses, the electrical grid at Arlanda and data provided by both the leading (electrical) bus manufacturers and the leading charging infrastructure manufacturers.  The outcome of this report suggests that a full electrification of the existing Alfa- and Beta line has the potential to lower CO2-emissions and energy use at a functional and cost effective way.

Energy efficiency within the transport sector - A case study on the vehicle fleet of a companyIsak EklövThe environmental objective of zero net emissions of greenhouse gases by 2045 asdecided by the Swedish parliament establishes a framework for a standard thatimplies a demand for considerable changes within many sectors at both technical and political level. The need for long term efficiency solutions with respect tosustainability to be able to reach this goal is great and one step towards this couldpotentially be an adaption to an increased amount of vehicles with alternative fuelsin the vehicle fleet of Sweden. This thesis examined the potential for companiesto reduce their life-cycle emissions of greenhouse gases as well as the total cost ofownership (TCO) for their vehicles by changing the composition of their vehiclefleet.The project started with a literature review of a general character where data forlife-cycle emissions of greenhouse gases as well as TCO for different vehicle typeswas examined and collected. Then the life-cycle emissions of greenhouse gases andTCO were calculated for the different vehicle types through a case study on thevehicle fleet of a company. Finally a programming script was developed to increasethe efficiency of the process which was then used to create scenarios with differentcompositions of the vehicle fleet. A sensitivity analysis was also carried out to evaluate the robustness of the life cycle calculations where the parameters individuallywere altered and the effect on the final result was examined.The result of the case study showed that alternative fueled vehicles are expected tolead to lower life-cycle emissions of greenhouse gases compared to the conventionalalternatives for all vehicle types where alternative fuels are commercially available.The only exception for this was the electric fringe benefit vehicle with a 100 kWhbattery which was expected to lead to higher life-cycle emissions than its fossilalternatives. The result of the cost analysis showed a similar pattern but in thiscase the service vehicle fueled with gas was expected to lead to a higher value ofTCO than its fossil alternatives. The sensitivity analysis for life-cycle emissionsof greenhouse gases showed that production of lithium-ion batteries, vehicle base production and tailpipe emissions were the most contributing parameters forfringe benefit vehicles. The purchase cost was found to be the most contributingparameter for TCO.The result of the scenario analysis showed that there is a potential to decreaseiiilife-cycle emissions of greenhouse gases by 22 % of the total life-cycle emissionsfor the vehicle fleet according to the Base-case scenario. The potential to decreaseTCO was found to be 1,1 %. The other scenarios showed a potential decrease forlife-cycle emissions of 37 % and a cost decrease of 7 % individually.Key words: greenhouse gas emissions, alternative fuels, electric vehicles, totalcost of ownership, life cycle assessment, sustainable vehicle fleet

The transport sector accounts for a third of Sweden’s total greenhouse gas emissions where cars and heavy trucks dominate the use of fossil fuels. The Swedish government is now intensifying the work for an electrified transport sector where electric roads could be an important part. Electric roads enable heavy vehicles to charge their batteries while driving, which is expected to contribute to environmentally friendly and time-efficient freight transports. To implement electric roads, availability of electric power along the electric roads will be required. This study presents a plan for connecting an electric road to the electricity grid in the electricity network area of Vattenfall Eldistribution. From the results, the idea was to present general conclusions from the experiences of the study, that could contribute in further implementation of electric roads.  The road that has been selected for the study was the E4 between Gävle and Stockholm. A model for calculating the power demand along the electric road has been modeled and connection possibilities to transformer stations has been investigated. The analysis was based on three scenarios where different degrees of strengthening of the existing electricity network were assumed. In addition, a forecast for 2030 and a cost estimation for each scenario has been carried out. The result of the study indicates that for road sections close to larger cities, there are a larger number of connection options in comparison to rural areas. Furthermore, the designed solution in the study required strengthening of the electricity grid and the investment cost was 362 million Swedish crowns.

The transport sector accounts for a third of Sweden’s total greenhouse gas emissions where cars and heavy trucks dominate the use of fossil fuels. The Swedish government is now intensifying the work for an electrified transport sector where electric roads could be an important part. Electric roads enable heavy vehicles to charge their batteries while driving, which is expected to contribute to environmentally friendly and time-efficient freight transports. To implement electric roads, availability of electric power along the electric roads will be required. This study presents a plan for connecting an electric road to the electricity grid in the electricity network area of Vattenfall Eldistribution. From the results, the idea was to present general conclusions from the experiences of the study, that could contribute in further implementation of electric roads. The road that has been selected for the study was the E4 between Gävle and Stockholm. A model for calculating the power demand along the electric road has been modeled and connection possibilities to transformer stations has been investigated. The analysis was based on three scenarios where different degrees of strengthening of the existing electricity network were assumed. In addition, a forecast for 2030 and a cost estimation for each scenario has been carried out. The result of the study indicates that for road sections close to larger cities, there are a larger number of connection options in comparison to rural areas. Furthermore, the designed solution in the study required strengthening of the electricity grid and the investment cost was 362 million Swedish crowns.

Controlling the balance of production and consumption of electricity will become increasingly challenging as the transport sector gradually converts to electric vehicles along with a growing share of wind power in the Swedish electric power system. This puts greater demand on resources that maintain the balance to ensure stable grid operation. The balancing act is called frequency regulation which historically has been performed almost entirely by hydropower. As the power production becomes more intermittent with renewable energy sources, frequency regulation will need to be performed in higher volumes on the demand side by having a more flexible consumption. In this report, the electrification of 17 buses Svealandstrafiken bus depot in Västerås has been studied. The aim has been to assess different charging strategies to efficiently utilize the available time and power but also to investigate if Svealandstrafiken can participate in frequency regulation. A smart charging model was created that demonstrated how smart charging can be implemented to optimize the charging in four different cases. The simulated cases were: charging with load balancing, reduced charging power, frequency regulation, and electrifying more buses. The results show that the power capacity limit will be exceeded if the buses are being charged directly as they arrive at the depot and without scheduling the charging session. By implementing smart charging, Svealandstrafiken can fully charge the 17 buses within the power capacity limit of the depot with 82 minutes to spare. By utilizing this 82-minute margin in the four different charging strategies, it was found that Svealandstrafiken can save 88 200SEK per year by load balancing, save 30 000 SEK per year by reducing the charging power by 10 %, earn 111 900 SEK per year by frequency regulation or electrify five more buses. Reducing the charging power may also increase the lifetime of the batteries but quantifying this needs further studies. Conclusively, there is economic potential for Svealandstrafiken for implementing smart charging.