<p dir="ltr">In this thesis, a MATLAB model was used to simulate a 2-vehicle platoon where the lead truck is a conventional class 8 vehicle while the key parameters of the following truck was tested in various road conditions to minimize Inter vehicular Distance (IVD) and maximize fuel savings while ensuring safety</p>

Submitted by Carlos Aurélio Bustamante Gonçalves (carlos.a.b.goncalves@gmail.com) on 2016-12-01T22:33:16Z No. of bitstreams: 1 carlos gonçalves - Dissertação - o mercado de caminhões no brasil -01122016.pdf: 3390001 bytes, checksum: df0eedc2484f2a8784dda76039181601 (MD5) / Rejected by Fabiana da Silva Segura (fabiana.segura@fgv.br), reason: Boa Noite, Prezado Carlos Peço corrigir alguns itens de formatação conforme segue: - Excluir o acento do nome Getulio nas páginas - Nome deve ser em maiúsculo (alternar, nas páginas que tiver o nome) - Titulo também em fonte maiúscula (alterar nas páginas que contém o título) - No rodapé permanece somente São Paulo - excluir o - SP - Linha de Pesquisa: Finanças e Economia de Empresas, alterar nas páginas que contém a lnha - Excluir na contra capa abaixo no nome do orientado FGV - EAESP - Folha de Assinaturas, alterar a linha de pesquisa e colocar a data de aprovação: 17/11/2016 Peço proceder com as alterações e submeter o trabalho novamente on 2016-12-01T23:28:13Z (GMT) / Submitted by Carlos Aurélio Bustamante Gonçalves (carlos.a.b.goncalves@gmail.com) on 2016-12-02T02:34:57Z No. of bitstreams: 1 carlos gonçalves - Dissertação - o mercado de caminhões no brasil -02122016.pdf: 3391454 bytes, checksum: 7cdcde7e62ecc28be15ec876866cca96 (MD5) / Approved for entry into archive by Fabiana da Silva Segura (fabiana.segura@fgv.br) on 2016-12-02T14:03:17Z (GMT) No. of bitstreams: 1 carlos gonçalves - Dissertação - o mercado de caminhões no brasil -02122016.pdf: 3391454 bytes, checksum: 7cdcde7e62ecc28be15ec876866cca96 (MD5) / Made available in DSpace on 2016-12-02T18:40:07Z (GMT). No. of bitstreams: 1 carlos gonçalves - Dissertação - o mercado de caminhões no brasil -02122016.pdf: 3391454 bytes, checksum: 7cdcde7e62ecc28be15ec876866cca96 (MD5) Previous issue date: 2016-11-17 / Este estudo trata do comportamento da demanda por caminhões novos no Brasil no período de 1996 a 2015 e da investigação dos fatores que a influenciam. Tal questão é relevante devido à escassez de estudos acerca deste tema, ainda que se trate do modo historicamente predominante de transporte de carga no país. O objetivo de pesquisa é determinar e quantificar os fatores que provocam o aumento ou diminuição das vendas de caminhão no Brasil. Para atingir este objetivo, foram construídos modelos econométricos a partir de dados secundários. Proxies utilizadas em outros modelos de demanda automotiva foram confirmadas e refinadas, enquanto novas proxies foram introduzidas com sucesso. Quanto aos resultados, este estudo inovou ao identificar três tipos de determinantes, e ao detalhar os efeitos e defasagens de suas influências: variáveis relacionadas especificamente ao mercado de caminhões, variáveis relacionadas ao PIB e variáveis relacionadas à confiança do comprador. Adicionalmente, realizou-se uma verificação da causalidade entre crédito e vendas, com o surpreendente resultado de que a influência ocorre no sentido de vendas para crédito. Com estes resultados, este estudo dissemina o conhecimento a respeito do comportamento do mercado a toda a cadeia produtiva, melhorando a qualidade das decisões e proporcionando aumento da eficiência para o sistema como um todo. / This is a study on the demand for new trucks in Brazil from 1996 to 2015, and an investigation on the factors that influence it. This topic is relevant due to the scarcity of studies concerning the subject, and due to the overwhelming domination of trucks in cargo transport in Brazil. It aims identify and quantify the variables that drive the sales of trucks. To reach this goal, econometric models were constructed based on secondary data. Variables usually adopted in other studies on automotive demand were confirmed and even refined and new variables were successfully introduced. This study innovates by identifying three groups of variables, and by detailing the effects and the lags of their influence: variables specific to the truck market, variables related to GDP, and variables related to the decision maker’s confidence. Additionally, a causality analysis involving credit and truck sales was performed, unexpectedly resulting in sales causing credit. Through these results, this study disseminates knowledge about the behavior of the truck market to the entire productive chain, contributing to evolve the quality of decisions and the efficiency of the entire system.

The large potential of big data and how it has brought value into various industries have been established in research. Since big data has such large potential if handled and analyzed in the right way, revealing information to support decision making in an organization, this thesis is conducted as a case study at an automotive manufacturer with access to large amounts of customer usage data of their vehicles. The reason for performing an analysis of this kind of data is based on the cornerstones of Total Quality Management with the end objective of increasing customer satisfaction of the concerned products or services. The case study includes a data analysis exploring how and if patterns about what affects fuel consumption can be revealed from aggregated customer usage data of trucks linked to truck applications. Based on the case study, conclusions are drawn about how a company can use this type of analysis as well as how to handle the data in order to turn it into business value. The data analysis reveals properties describing truck usage using Factor Analysis and Principal Component Analysis. Especially one property is concluded to be important as it appears in the result of both techniques. Based on these properties the trucks are clustered using k-means and Hierarchical Clustering which shows groups of trucks where the importance of the properties varies. Due to the homogeneity and complexity of the chosen data, the clusters of trucks cannot be linked to truck applications. This would require data that is more easily interpretable. Finally, the importance for fuel consumption in the clusters is explored using model estimation. A comparison of Principal Component Regression (PCR) and the two regularization techniques Lasso and Elastic Net is made. PCR results in poor models difficult to evaluate. The two regularization techniques however outperform PCR, both giving a higher and very similar explained variance. The three techniques do not show obvious similarities in the models and no conclusions can therefore be drawn concerning what is important for fuel consumption. During the data analysis many problems with the data are discovered, which are linked to managerial and technical issues of big data. This leads to for example that some of the parameters interesting for the analysis cannot be used and this is likely to have an impact on the inability to get unanimous results in the model estimations. It is also concluded that the data was not originally intended for this type of analysis of large populations, but rather for testing and engineering purposes. Nevertheless, this type of data still contains valuable information and can be used if managed in the right way. From the case study it can be concluded that in order to use the data for more advanced analysis a big-data plan is needed at a strategic level in the organization. The plan summarizes the suggested solution for the managerial issues of the big data for the organization. This plan describes how to handle the data, how the analytic models revealing the information should be designed and the tools and organizational capabilities needed to support the people using the information.

Hochsch. für Wirtschafts-, Rechts- und Sozialwiss., Diss.--St. Gallen, 2007.

La conduite d’un véhicule industriel est une activité professionnelle complexe qui s’exerce dans un environnement dynamique en constante évolution. Elle nécessite un apprentissage spécifique et se situe dans un cadre réglementaire strict, qui relève aussi bien du code du travail que de la réglementation routière. A ces caractéristiques s’ajoutent de fortes contraintes spatio-temporelles qui imposent aux conducteurs le recours à des stratégies opératoires pour répondre à l’objectif principal de leur activité : le respect des délais de livraison dans des conditions optimales de sécurité, de sûreté et de productivité.Cette thèse traite de l'apport de la psychologie cognitive à la conception de systèmes d'assistance à la conduite de véhicules industriels. Les travaux sont destinés à intégrer, dès la conception des nouveaux systèmes, les contraintes du fonctionnement cognitif humain en situation réelle, ainsi que les besoins et attentes des conducteurs, afin que leur soient proposées des solutions technologiques adaptées et utilisables.La partie appliquée illustre deux dimensions majeures de l'activité de conduite d'un camion : la productivité, au travers de la problématique de l'assistance à l'éco-conduite (projet Conduite Economique Assistée, ADEME- RENAULT TRUCKS) ; la sécurité, au travers de la problématique de l'assistance à la détection et à la protection des usagers vulnérables de la route (projet VIVRE2, ANR-PREDIT05-LUTB).D’un point de vue scientifique, la thèse aboutit à la proposition d’un modèle du fonctionnement humain dans les activités finalisées, complété par un modèle adapté à l’activité de conduite d’un véhicule industriel. Les analyses effectuées en situations réelles enrichissent les connaissances, d’une part, sur les stratégies de conduite appliquées à la conduite rationnelle d’un poids lourd en environnement extra-urbain, et, d’autre part, sur les composantes de l’activité des conducteurs qui effectuent des livraisons en milieu urbain. De plus, les travaux effectués dans le cadre du projet VIVRE2 ont permis de préciser les représentations et les comportements à risque des usagers vulnérables vis-à-vis des camions en ville.D’un point de vue applicatif et ergonomique, les travaux sur simulateur dynamique de conduite ont permis l’évaluation d’une interface homme-machine innovante qui pourrait être adaptée à l’éco-conduite, ainsi que la proposition et l’évaluation de systèmes d’assistance pour garantir la sécurité des usagers vulnérables lors des manœuvres à basse vitesse en milieu urbain. / Driving a truck is a complex professional activity that takes place in a dynamic and constant changing environment. It needs a specific learning and it is set in a strict regulated framework including French labour code (Code du travail) as road regulation. Strong spatio-temporal pressure should be added to those characteristics. These constraints entail to drivers the use of operative strategies to achieve the main objective of their activity: respect of delivery time in optimal conditions of safety, security and productivity.This thesis deals with the contribution of cognitive psychology to the design of driving assistance systems for trucks. Works are intended to integrate, from the design of new systems, the demands of human cognitive functioning in real situation and the needs and expectations of drivers so that adapted and usable technological solutions could be proposed to them.Applied part shows two major dimensions of truck driving activity: productivity through the issue of the eco-driving assistance (“Conduite Economique Assistée, ADEME- RENAULT TRUCKS” project) and safety through the issue of the assistance to detection and protection of vulnerable road users (“VIVRE2, ANR-PREDIT05-LUTB” project).From a scientific point of view, the thesis ends with a proposal of a model of human functioning in finalized activities, of which is added an adapted model of the truck driving activity. The analysis performed in real environment enhance knowledge, on the one hand, on the applied driving strategies to the eco-driving of a truck in extra-urban environment and, on the other hand, on the components of the activity of drivers doing deliveries in urban environment. Moreover, works performed in VIVRE2 project allowed to specify representations and risky behaviours of vulnerable users with relation to trucks in town.From an applicative and ergonomic point of view, works on driving dynamic simulator allowed the evaluation of an innovative man-machine interface which could be adapted to eco-driving and the proposal as well as the evaluation of assistance systems to guarantee safety of vulnerable users during low speed manoeuvres in urban environment.

Battery electric trucks (BETs) offer environmental benefits in terms of reduced carbon emissions and enhanced energy efficiency but have been challenged with economic viability compared to conventional internal combustion engine trucks (ICETs) caused by substantial acquisition costs, limited charging infrastructure, and concerns regarding range and payload capacity.  Previous studies focus on TCO at the vehicle or policy level but overlook the system and firm-level impacts. Operational aspects like vehicle utilization, battery utilization, charging planning, and route optimization are often ignored, potentially underestimating electric freight cost-competitiveness.The research gap does not address the practical needs of fleet operators, especially in scenarios where charging infrastructure is lacking. There is therefore a need to consider the complex system level interactions, market dynamics, technology developments, and operational processes involved in freight shipping. By applying a decision-making under deep uncertainty (DMDU) framework, this study enables informed decisions in unpredictable scenarios, bridging the gap between strategic choices like battery capacity and operational optimization like route planning. This study identifies the most significant factors that affect the TCO of BET fleets and cost-competitiveness relative to ICET fleets, taking into account market-operational interfaces between unpredictable market dynamics and operational processes such as stochastic demand and feature selection from a strategic and operational perspective. 40 tonne truck-trailers for freight distribution networks with distances up to 250 km are considered in the study.  A TCO model of BET and ICET fleets was developed taking into account vehicle route optimization, vehicle selection, and vehicle utilization which was then programmatically iterated by sampling and simulating optimized vehicle routes for a total of 220 224 iterations. The parameter space was screened and reduced with Feature Scoring using Extra Trees approximation of 1st order Sobol Indices. The reduced parameter space was then sampled using Sobol sampling to conduct a Sobol Global Variance decomposition Analysis of TCO, TCO delta, and service level in order to identify the most significant factors affecting BET fleet TCO and cost-competitiveness.To identify cost-competitive scenarios, the Patient Rule Induction Method (PRIM) was used to identify parameter sub spaces to determine scenarios where BET fleets have a lower TCO than ICET fleets. Further visual analysis was done using linear and polynomial regression and kernel density estimation. The analysis shows that both TCO and cost-competitiveness of BETs are primarily affected by shipment demand, distance between distribution center and delivery sites, and battery size, and that a trade-off is made between cost-competitiveness and service level. The results show that cost-competitiveness of electric freight scales with demand, with larger fleets being better able to optimize routing and shipment allocation; balancing the shipment demand to minimize charging times that otherwise would make the fleet less competitive than their fossil-fuel counterparts. This, paired together with higher degrees of vehicle utilization and appropriate battery sizing, allow for electric freight to be cost-competitive even for long-haul distances up to 250 km.  Furthermore, optimization of the Electric Vehicle Routing Problem (E-VRP) with shifts and time windows is shown to have a highly significant effect when minimizing TCO on a fleet level, with the vast majority of optimal ICET routes not being optimal for BETs.The benefits of E-VRP optimization scales with demand and fleet size, indicating that large-scale electrification is required to make BETs cost-competitive.Electrification of road freight is therefore highly contingent on effective route planning and charging scheduling with E-VRP optimization in order to be cost-competitive, which has not been considered in previous literature. Thus previous literature have therefore likely underestimated the cost-competitiveness of electric freight, particularly at medium-long haul distances. / Battery electric trucks (BETs), även kända som batterielektriska lastbilar, erbjuder miljömässiga fördelar genom minskade koldioxidutsläpp och förbättrad energieffektivitet. Men de har utmanats när det kommer till ekonomisk konkurrenskraft jämfört med konventionella lastbilar med förbränningsmotor (ICETs) på grund av höga inköpskostnader, begränsad laddinfrastruktur och oro över räckvidd och lastkapacitet. Tidigare studier har fokuserat på TCO (totala ägandekostnader) på fordon- eller policynivå men har inte betraktat TCO på nätverksnivå och från det enskilda företagets perspektiv. Operativa aspekter som fordonssutnyttjande, batteriutnyttjande, laddningsplanering och ruttoptimisering ignoreras ofta, vilket potentiellt leder till en underskattning av elektrisk frakts kostnadskonkurrenskraft. Forskningsluckan tar inte upp de praktiska behoven hos fordonsflottoperatörer, särskilt i scenarier där laddinfrastrukturen är bristfällig. Det finns därför ett behov av att granska komplexa systemnivåinteraktioner, marknadens dynamik, teknikutveckling och operativa processer som är involverade i godstransport. Genom att tillämpa \textit{decision-making under deep uncertainty} (DMDU) möjliggör denna studie informerade beslut i scenarier präglade av osäkerhet och studerar interaktionseffecter mellan strategiska val som batterikapacitet och operativ optimering som t.ex.\ ruttplanering. Denna studie identifierar de mest betydande faktorer som påverkar TCO för BET-flottor och deras kostnadskonkurrenskraft jämfört med ICET-flottor, med beaktande av gränssnitten mellan marknadsdynamik och operativa processer såsom stokastisk efterfrågan och urval av funktioner ur såväl strategisk som operativ synvinkel. 40-ton lastbilssläp för nätverk med avstånd upp till 250 km beaktas inom omfånget för studien. En TCO-modell för BET- och ICET-flottor utvecklades med hänsyn till ruttoptimering, fordonsval och fordonsutnyttjande, vilket sedan programmässigt itererades genom provtagning och simulering av optimerade fordonsrutter för sammanlagt 220 224 iterationer. Parameterrummet granskades och minskades med hjälp av funktionsskattning med hjälp av Extra Trees-approximation av Sobol-indices av första ordningen. Det reducerade parameterrummet provtogs sedan med Sobol-provtagningsmetod för att genomföra en global variansdekomponering av TCO, TCO-delta och servicenivå för att identifiera de mest betydande faktorerna som påverkar BET-flottans TCO och kostnadskonkurrenskraft. För att identifiera kostnadskonkurrenskraftiga scenarier användes Patient Rule Induction Method (PRIM) för att identifiera parametrarum som visar scenarier där BET-flottor har lägre TCO än ICET-flottor. Vidare utfördes visuell analys med linjär och polynomisk regression samt kärnskattning. Analysen visar at kostnadskonkurrenskraft för tunga elektriska fordon primärt påverkas av efterfrågan, köravstånder och batteristorlek, och att det görs en avvägning mellan kostnadskonkurrenskraft och servicenivå. Resultaten visar at kostnadskonkurrenskraft ökar i takt med efterfrågan, då större flottor kan mer fördelaktigt optimera rutter och allokering av leveranser till varje fordon genom att transportefterfrågan balanseras sådan att tiden för laddning minimeras, vilket hade annars gjort de elektriska flottorna mindre konkurrenskraftiga gentemot fossildrivna flottor av tunga fordon. Detta i samband med högre utnyttjandegrad av fordonen och val av rätt batteristorlek gjör att elektrisk godstransport kan vara kostnadskonkurrenskraftig även vid längre körsträckor upp till 250 km. Vidare visar ruttoptimering för BETs (E-VRP) sig vara av stor betydelse när det gäller att minimera TCO på flottnivå, medan majoriteten av optimala ICET-rutter inte är optimala för BETs.Fördelarna med E-VRP optimering skalar med ökande efterfrågan och flottstorlek, vilket tyder på att storskalig elektrifiering behövs för att göra BETs kostnadskonkurrenskraftigaElektrifiering av godstransport är därför starkt beroende av effektiv rutt- och laddningsplanering med E-VRP-optimering. Tidigare litteratur har sannolikt underskattat kostnadskonkurrenskraften för elektrisk godstransport, särskilt vid medellånga och långa transportavstånd.

The recent climate actions to reduce greenhouse gas (GHG) emissions have set the stage for decarbonizing the transportation sector through electrification, which has led to a surge in the deployment of battery electric vehicles (BEV). Trucks are no exception, which has led automakers to shift their focus toward producing Battery Electric Trucks (BET). While tail-pipe emissions are reduced drastically, certain aspects of BET prevent its widespread deployment, prominent of which is the range anxiety. The range of a BET is heavily impacted in cold weather as energy from traction batteries is also used to warm the battery pack and cabin, where 70% of cabin airflow at minimum is continually expelled through exhaust vents for proper ventilation. In this study, three heat recovery techniques were investigated with the objective of harnessing the waste heat from evacuating cabin air to reduce the heating energy consumption in a BET. One proposed technique employs the use of an air-to-air heat recovery system (AAHRS). Baseline experiments were conducted on a SCANIA test truck for benchmarking and to gather data on the performance of the installed HVAC system, which aided the prototyping stage of basic engineering design to ensure it is operable and safe. The prototype was modelled in CATIA, then fabricated and fitted to the test-truck. Validation experiments were done to evaluate the energy savings from the prototype in a climate chamber at various ambient temperature and fan speed settings. The study found a 20-53% reduction in the heat dissipated by the coolant with the implementation of AAHRS, which is beneficial in reducing the energy that need to be replenished by electric batteries for a BET. In contrast, the electrical power consumption increased 1.7-3.3 times higher than the baseline due to the additional power-consuming components, such as the exhaust blower and heat wheel motor. Moreover, the preheating effect from the heat wheel operation enabled the increase of HVAC air intake temperature by 7-28°C from ambient levels. Overall, the energy savings from integrating the AAHRS prototype was about 19-47% considering the coolant heat was produced from an electric heater as was simulated in the tests, whereas the range was estimated to reduce by17-39% if an automotive heat pump would instead deliver the heat into the cab heater core. Two other presented techniques operate on air-to-liquid heat recovery system (ALHRS), whereby each is envisioned to be coupled separately to a heat pump assisted integrated thermal management system (ITMS). One scheme recovers heat from the evacuating cabin air to raise the chiller coolant inlet temperature, whereas the other scheme proposes to adopt a multi-evaporation process in the concept liquid-cooled heat pump, wherein the evacuating cabin air serves as the direct heat source for the higher temperature-chiller. The two schemes were initially evaluated via vapor compression system performance analysis to have the potential to increase the condensation heat and condenser coolant outlet temperature with simultaneous increase in the coefficient of performance, which is beneficial in terms of available heat that can be dissipated into the downstream battery cold plates and cab heater core. As initial step towards assessment of the energy-saving potential of proposed ALHRS solutions, a simulation model of an adopted baseline ITMS concept was developed in this study using Engineering Equation Solver (EES) software, which then was validated against internal bench test results for a mock-up ITMS model. Results of initial validation test indicated an absolute error between the simulation outputs and bench test results of 8-14% for condensation heat, while it was below 7% for all the other relevant performance parameters. / De senaste klimatåtgärderna för att minska utsläppen av växthusgaser (GHG) har satt scenen för att minska koldioxidutsläppen inom transportsektorn genom elektrifiering, vilket har lett till en kraftig ökning av utbyggnaden av batterielektriska fordon (BEV). Lastbilar är inget undantag, vilket har fått biltillverkare att flytta fokus mot att producera batterielektriska lastbilar (BET). Medan utsläppen från avgasröret minskar drastiskt, förhindrar vissa aspekter av BET dess utbredda distribution, varav framträdande är räckviddsångesten. Räckvidden för en BET påverkas kraftigt i kallt väder eftersom energi från dragbatterier också används för att värma batteripaketet och kabinen, där minst 70% av kabinluftflödet kontinuerligt släpps ut genom avgasventiler för korrekt ventilation. I denna studie undersöktes tre värmeåtervinningstekniker med målet att utnyttja spillvärmen från evakuering av kabinluft för att minska värmeenergiförbrukning i en BET. En föreslagen teknik använder användning av ett luft-till-luft-värmeåtervinningssystem (AAHRS). Baslinjeexperiment utfördes på en SCANIA-testbil för benchmarking och för att samla in data om prestandan hos det installerade HVAC-systemet, vilket hjälpte prototypstadiet för grundläggande teknisk design för att säkerställa att det är funktionsdugligt och säkert. Prototypen modellerades i CATIA, tillverkades sedan och monterades på testbilen. Valideringsexperiment utfördes för att utvärdera energibesparingarna från prototypen i en klimatkammare under olika inställningar för omgivningstemperatur och fläkthastighet. Studien fann en 20-53% minskning av värmebelastningen med implementeringen av AAHRS, vilket är fördelaktigt för att minska energin som behöver fyllas på av elektriska batterier för en BET. Däremot ökade den elektriska strömförbrukningen 1.7-3.3 gånger högre än baslinjen på grund av ytterligare strömförbrukande komponenter, såsom avgasfläkten och värmehjulsmotorn. Dessutom möjliggjorde förvärmningseffekten från värmehjulsdrift ökningen av HVAC-luftintagstemperaturen med 7-28°C från omgivande nivåer. Sammantaget var energibesparingarna från att integrera AAHRS-prototypen cirka 19-47% med tanke på att kylvätskevärmen producerades från elektrisk värmare som simulerades i experimenten, medan detta intervall uppskattades minska ner till 17-39% om en bilvärmepump istället skulle leverera värmen till hyttvärmarkärnan. Två andra presenterade tekniker fungerar på luft-till-vätska värmeåtervinningssystem (ALHRS), där var och en är tänkt att kopplas separat till ett värmepumpassisterat integrerat värmehanteringssystem (ITMS). Det ena schemat återvinner värme från den evakuerande kabinluften för att höja kylvätskeinloppstemperaturen, medan det andra schemat föreslår att man antar en multiindunstningsprocess i konceptet vätskekyld värmepump, där den evakuerande kabinluften fungerar som den direkta värmekällan för kylaggregatet med högre temperatur. De två scheman utvärderades initialt via ångkompressionssystemets prestandaanalys för att ha potential att öka kondensationsvärmen och kondensorns kylvätskeutloppstemperatur med samtidig ökning av prestandakoefficienten, vilket är fördelaktigt när det gäller tillgänglig värme som kan avledas i nedströms batteriets kylplattor och hyttvärmarens kärna. Som ett första steg mot en bedömning av energibesparingspotentialen hos föreslagna ALHRS-lösningar utvecklades en simuleringsmodell av ett antaget baslinje-ITMS-koncept i denna studie med hjälp av Engineering Equation Solver (EES) -programvara, som sedan validerades mot interna bänktestresultat för en mock-up ITMS-modell. Resultaten av det inledande valideringstestet indikerade ett absolut fel mellan simuleringsutgångarna och provbänksresultaten på 8–14% för kondensationsvärme, medan det var under 7 % för alla andra relevanta prestandaparametrar.

Transporter står idag för en stor andel av Sveriges koldioxidutsläpp. Det gör att logistikfrågor blir extra viktiga då vidareutveckling och omformning av logistiksystem kan göra stor skillnad. Elektrifiering av fordon är en framtida lösning på problemet. Däremot anses det fortfarande vara ett förhållandevis nytt och osäkert område och det finns idag få exempel på implementering av elektrifierade fordon. Transportören Renall och transportköparen Returpack är två framstående företag med starkt hållbarhetsfokus som agerar fallföretag för studien. De har högt uppsatta mål, däribland elektrifiering av en stor andel av sina fordonsflottor till 2030. Studiens syfte är därför formulerat som följande: Syftet är att utreda hur transportörer och transportköpare kan arbeta mot fullständig elektrifiering av tunga transporter. Studien är uppdelad i tre primära delar. Den första delen utvecklar en metodik för hur elektrifierade fordon ska implementeras i verksamheter för att sedan kunna skalas upp. Denna metodik har resulterat i tre primära delar. Den första delen är utformning av ett elektrifierat logistiksystem där större strukturförändringar i logistiksystemet måste göras med syfte att öka effektivitet, nyttjandegrad och förutsägbarhet. Den andra delen är utformning av fordonsflotta där beslut om lämpliga batterikapaciteter för varje enskilt fordon tas. Den tredje delen utformning av laddstrategi beslutar om lämplig laddstrategi utifrån fordons- och uppdragskarakteristik. Den utformade metodiken appliceras sedan på fallföretagens presenterade empiri för att resultera i rekommendationer för hur de bör utforma sina elektrifierade logistiksystem, fordonsflottor samt laddstrategier. Efter analys av lösningar som ämnar anpassa logistiksystemet till elektrifiering presenteras rekommendationer för fallföretagen utifrån deras specifika situationer. Det kan dock konstateras att en stark maktposition, ett välutvecklat systemstöd samt kompetens inom elektrifiering underlättar arbetet mot ett elektrifierat logistiksystem. Vid utformning av fordonsflottan presenteras det samlade resultatet av ekonomiska analyser samt bedömningar av genomförbarheten för respektive fordon. Resultatet påvisar att det för cirka hälften av fordonen är ekonomiskt fördelaktigt med ett mindre batteri men att detta oftast begränsas av brist på laddinfrastruktur och behov av flexibilitet vilket innebär behov av överdimensionering. Det samlade resultatet innebär att cirka 20% av fordonsflottan rekommenderas mindre batterier. Vid utveckling av laddstrategier är rekommendationerna liknande för fallföretagen vilket beror på att en laddstrategi är beroende av enskilda fordons karakteristik snarare än en aktörs roll. Fallföretagen rekommenderas att utveckla två primära laddstrategier: en return to base strategi för laddning mellan skift samt en on route strategi för laddning under pågående rutt. Därtill utvecklas även en kostnadsmodell för att kunna genomföra en kostnadsanalys av hur kostnader förändras vid byte från nuvarande bränsle till elektrifierad drivlina. Den visar att sänkning eller höjning av kostnader vid byte av drivlina varierar mellan olika fordonstyper och områden, men att lönsamhet kan uppnås i många fall. Däremot krävs ibland justeringar och förändringar av logistiksystemet. Främst ses att långa avtalsperioder och hög nyttjandegrad av fordonen är att föredra. Likaså ger minskade inköpspriser stort utslag på resultatet. / Transport related activities currently account for a significant portion of Sweden’s carbon dioxide emissions. This makes logistics issues particularly important, as further development and transformation of logistics systems can make a big difference. Electrification of heavy trucks is a future solution to the problem. However, it is still considered a relatively new and uncertain area, and there are currently few examples of the implementation of electrified heavy trucks. The carrier Renall and the transport buyer Returpack are two prominent companies with a strong sustainability focus, acting as case companies for the study. They have currently set ambitious goals, including electrifying a large portion of their heavy truck fleets by the year 2030. Therefore, the purpose of the study is formulated as follows: The purpose is to investigate how carriers’ and transport buyers’ can work towards complete electrification of heavy transports. The study is divided into three primary parts. The first part develops a methodology for implementing electrified heavy trucks in operations, with the goal of scalability. This methodology has resulted in three sub-parts. The first sub-part is the design of an electrified logistics system, where significant structural changes in the logistics system are necessary to increase efficiency, utilization, and predictability. The second sub-part involves designing the heavy truck fleet, including decisions on appropriate battery capacities for each individual heavy truck. The third sub-part focuses on designing a charging strategy based on truck and mission characteristics. The formulated methodology is then applied to the empirical data presented by the case companies, resulting in recommendations on how they should design their electrified logistics systems, heavy truck fleets, and charging strategies. Solutions aimed at adapting the logistics system to electrification are analyzed, which result in recommendations for the case companies based on their specific situations. However, it can be noted that a strong market position, well-developed system support, and knowledge in electrification can ease the transition to an electrified logistics system.In the design of the heavy truck fleet, the combined results of economic analyses and feasibility assessments for each vehicle are presented. The results indicate that for approximately half of the vehicles, it is economically advantageous to have a smaller battery. However, this is often limited by a lack of charging infrastructure and the need for flexibility, which necessitate overdimensioning. The combined result is that approximately 20% of the vehicle fleet is recommended to have smaller batteries.In the development of charging strategies, the recommendations are similar for the case companies, as a charging strategy depends on the characteristics of individual vehicles rather than the role of the operator. The case companies are recommended to develop two primary charging strategies: a return to base strategy for charging between shifts and an on route strategy for charging during the ongoing route. Lastly, a cost model is developed to conduct a cost analysis of how expenses change when transitioning from heavy trucks fueled by HVO or biogas to electrified heavy trucks. It shows that cost reduction or cost increase upon fuel conversion varies among different truck types and regions, but profitability can be achieved in many cases. However, adjustments and changes to the logistics system are sometimes necessary. Long contract periods and high vehicle utilization are particularly favorable. Similarly, reduced purchase prices have a significant impact on the outcome.

There has recently been an increased interest in hydrogen, both as a solution for seasonal energy storage but also for implementations in various industries and as fuel for vehicles. The transition to a society less dependent on fossil fuels highlights the need for new solutions where hydrogen is predicted to play a key role. This project aims to investigate technical and economic outcomes of different strategies for production and storage of hydrogen based on hydrogen demand and source of electricity. This is done by simulating the operation of different systems over a year, mapping the storage level, the source of electricity, and calculating the levelized cost of hydrogen (LCOH). The study examines two main cases. The first case is a system integrated with offshore wind power for production of hydrogen to fuel the operations in the industrial port Gävle Hamn. The second case examines a system for independent refueling stations where two locations with different electricity prices and traffic flows are analyzed. Factors such as demand, electricity prices, and component costs are investigated through simulating cases as well as a sensitivity analysis. Future potential sources of income are also analyzed and discussed. The results show that using an alkaline electrolyzer (AEL) achieves the lowest LCOH while PEM electrolyzer is more flexible in its operation which enables the system to utilize more electricity from the offshore wind power. When the cost of wind electricity exceeds the average electricity price on the grid, a higher share of wind electricity relative to electricity from the grid being utilized in the production results in a higher LCOH. The optimal design of the storage depends on the demand, where using vessels above ground is the most beneficial option for smaller systems and larger systems benefit financially from using a lined rock cavern (LRC). Hence, the optimal design of a system depends on the demand, electricity source, and ultimately on the purpose of the system. The results show great potential for future implementation of hydrogen systems integrated with wind power. Considering the increased share of wind electricity in the energy system and the expected growth of the hydrogen market, these are results worth acknowledging in future projects.

<p>Food trucks have become increasingly popular over the last decade following the Great Recession of 2008. Scholars have begun to study the food truck phenomenon, its future projected trajectory, and even positioning it within social justice discourse along cultural lines; however, scholarship has yet to address the participation of Black entrepreneurs in the food truck industry.</p> <p><br></p> <p>The objective of this dissertation is to expand the perception of Black food entrepreneurs within the food truck industry by interrogating how Black food truck owners are misrepresented, under analyzed, and underestimated. Using a series of interdisciplinary qualitative methods including introspective analysis, thematic coding analysis, and case studies, I approach this objective by addressing three questions. First, I analyze movies and television to understand where Black-owned food trucks are represented in popular culture and how they are depicted. In doing so, we come to understand that Black business representation, specifically Black food truck representation consistently falls victim to negative stereotypes. These stereotypes can influence the extent to which Black food truck owners are taken seriously and seen as legitimate business leaders in their community. Second, I interview 16 Black food truck entrepreneurs to understand why the mobile food industry appealed to them and how it has become a platform for them to explore other opportunities. Finally, I review eight cities that have launched Black food truck festivals and parks within the last 6 years to gain an understanding of the collective power wielded by Black food truck owners and its impact Black communities. Moreover, this dissertation challenges the myth that collectivism does not exist among Black entrepreneurs and the Black community broadly.</p>