Post on 16-Jul-2020
Deterministic and Stochastic Total Cost of Ownership(TCO) Analysis for commercial vehicles in Germany
Master Thesis Presentation
Hiteshkumar Amipara
Renewable Energy and Energy Efficiency for the Middle East and North Africa Region [REMENA]University of Kassel
March 5, 2019
Hiteshkumar Amipara TCO March 5, 2019 1 / 61
Table of Contents
Table of Contents
1 Introduction
2 Methodology
3 Results
4 Conclusions and Future Work
5 References
Hiteshkumar Amipara TCO March 5, 2019 2 / 61
Introduction
Table of Contents
1 IntroductionMotivationThesis Contribution
2 MethodologyTCO calculation structureVehicle drivetrains and segmentsDeterministic TCO analysisValidationStochastic TCO analysis
3 ResultsDeterministic TCOStochastic TCO
4 Conclusions and Future Work
5 References
Hiteshkumar Amipara TCO March 5, 2019 3 / 61
Introduction Motivation
Motivation
The transport sector is the third largest cause of 160 million tonnes of CO2
emission in 2015 [25].
Increasing road freight vehicles with Low-efficiency improvements and low fuelprices have led to increase emissions in 2016.
Government of Germany has decided the national goal to decrease greenhousegas (GHG) emissions 40 % by 2020, 50 % by 2030, and 80-95 % by 2050(compared to 1990) [1].
Electric vehicles fuelled by renewable energy sources are expected to reduce CO2
emissions in commercial vehicle areas.
Majority of existing Total cost ownership (TCO) studies: Deterministic inputparameters.
Hiteshkumar Amipara TCO March 5, 2019 4 / 61
Introduction Thesis Contribution
Thesis Contribution
Provide a deterministic and stochastic TCO comparison among three drivetraintechnologies for commercial vehicles in Germany from 2020 to 2030.
Effect of additional storage weight (drivetrain characteristics, daily mileage) ontransport capacity.
Hiteshkumar Amipara TCO March 5, 2019 5 / 61
Methodology TCO calculation structure
Table of Contents
1 IntroductionMotivationThesis Contribution
2 MethodologyTCO calculation structureVehicle drivetrains and segmentsDeterministic TCO analysisValidationStochastic TCO analysis
3 ResultsDeterministic TCOStochastic TCO
4 Conclusions and Future Work
5 References
Hiteshkumar Amipara TCO March 5, 2019 6 / 61
Methodology TCO calculation structure
TCO calculation structure of each vehicle
Figure: TCO calculation structure [4]
TCO is spilt into CAPEX andOPEX.
CAPEX has the initial purchasingprice (IPP) and resale price.
OPEX includes fixed cost andvariable cost.
Hiteshkumar Amipara TCO March 5, 2019 7 / 61
Methodology Vehicle drivetrains and segments
Vehicle drivetrains and segments
Three drivetrain technologies
Internal combustion engine vehicle(ICEV), Battery electric vehicle (BEV),Fuel cell electric vehicle (FCEV)
Figure: Vehicle drivetrains
Vehiclesegment
Vehicle segmentshare
Categories 1 Passenger car 26 %Categories 2 Local bus -
Categories 3LDV 75%MDV 7%HDV 9%
Categories 4MHV(Class-1) -MHV(Class-2) -MHV(Class-3) -
Table: Vehicle segments [2][3]
Four vehicle segments
Passenger car, Local bus
Road freight vehicles: Light-dutyvehicle (LDV), Medium duty vehicle(MDV), Heavy-duty vehicle (HDV)
Material handling vehicle (MHV)Go to
Hiteshkumar Amipara TCO March 5, 2019 8 / 61
Methodology Deterministic TCO analysis
Deterministic TCO analysis
Figure: Workflow of the deterministic TCO analysis
TCO defined as T :
T =
(I −RP )C + 1N
N∑n=1
Aoc(1+i)n
A(1)
where,
T : total cost of ownership in e/kmor e/h
I: initial purchasing price (IPP) ine
A: could be AK (annual kilometerstravelled) in km or AH (annualworking hours) in h
Aoc: annual operating cost in e
R: resale price in e
C: capital recovery factor
P : present value factor
N : vehicle holding period of thefirst owner in years
i: interest rate in %
Hiteshkumar Amipara TCO March 5, 2019 9 / 61
Methodology Deterministic TCO analysis
Input parameters: Investment cost of the vehicle components
Component Description Unit 2020 2025 2030Drivetrain Combustion engine e/kW 60 63.5 67
Electric motor e/kW 18 16 14PEM fuel cell system e/kW 180 65 35
Energystorage
Hydrogen storagetank
e/kWh 11.4 10.26 9.12
Li-ion battery pack e/kWh 155 105 90Miscellaneous Converter, Controller,
Invertere/kW 24 21 18
Table: Investment cost of different vehicle components [6][7][11][14]
Battery pack cost decreases over the years due to the rising production units, aswell as technology improvements.
Fuel cell system cost decreases rapidly.
Internal combustion engine costs are expected to increase over time.
Go to
Hiteshkumar Amipara TCO March 5, 2019 10 / 61
Methodology Deterministic TCO analysis
Input parameters: Investment cost of different vehiclecomponents
Vehiclesegment
Body cost [e] Daily meanmileage [km]
Categories 1 Car 9468 100Categories 2 Bus 240000 243
Categories 3LDV 20000 88MDV 40000 225HDV 60000 430
Categories 4MHV(Class-1) 25000 -MHV(Class-2) 25000 -MHV(Class-3) 7800 -
Table: Input parameters [4][5][12]
Body cost is determined so that estimated values match real sale price.
ValueNumber of shifts per day 2Number of hours per shift 7.25Annual working hours 2000
Table: Vehicle usage parameters for MHV (Class-1,2,and 3) [16]
Hiteshkumar Amipara TCO March 5, 2019 11 / 61
Methodology Deterministic TCO analysis
Initial purchasing price (IPP) and storage capacity:′′Bottom-up approach′′
Figure: Workflow of IPP (Bottom-up approach)
Figure: Vehicle drivetrains
IPP is calculated using the followingequation :
I = PcRp (2)
where,
I: initial purchasing price in e
Pc: production cost in e
Rp: retail price equivalent factor
The power of engine, electric motor and fuel cell system is based on referencevehicle.
Hiteshkumar Amipara TCO March 5, 2019 12 / 61
Methodology Deterministic TCO analysis
Structure of Initial purchasing price
Figure: Structure of Initial purchasing price
IPP was calculated at a dailymileage of 300 km.
FCEV has the IPP of 54,995e with storage cost 1,491 e.
BEV has the IPP of 35,797 ewith storage cost 15,295 e.
ICEV has the IPP of 25,165e.
Hiteshkumar Amipara TCO March 5, 2019 13 / 61
Methodology Deterministic TCO analysis
Resale price of the Vehicle
Resale price (R) in e for passenger car [17]:
R = eαe12β1LeAKβ2
12 Iβ3 (3)
where,
α: absolute term
β1,β2, β3:coefficient estimators
L: lifetime of vehicle in year
R in e for the local bus and road freight vehicle can be determined by followingequation [18]:
R = 0.10I (4)
Hiteshkumar Amipara TCO March 5, 2019 14 / 61
Methodology Deterministic TCO analysis
Operating expenditures (OPEX) calculation
Figure: Structure of OPEX
Fuel 2020 2025 2030Energycarrierprice
Diesel(e/L)
1.37 1.635 1.9
Electricity(e/kWh)
0.217 0.234 0.250
Hydrogen(e/kg)
12.62 11.309 10.65
Table: Fuel price [7][19]
Go to
Energy cost is the largest share of the vehicle′s operating cost.
The energy consumption data of passenger car, local bus and MHV is based on areview of the literature sources.
For road freight vehicle, a linear regression analysis is used to calculate the fuelconsumption.
Hiteshkumar Amipara TCO March 5, 2019 15 / 61
Methodology Deterministic TCO analysis
Additional weight effect of a battery electric versusconventional drivetrain
Figure: Battery pack density impacts on BEB weight andrange
Parameters ValueEnergy consumption for battery electricbus at the wheels (kWh/km)
1.5
Mean Mileage (km) 243Battery pack size (kWh) 455.62Energy density of battery pack (Wh/kg) 235Battery pack weight (kg) 1938.8Power of electric motor for bus (kW) 150Weight of electric motor (kg) 30Total weight of battery and motor (kg) 1968.8Energy consumption for diesel bus(kWh/km)
4
Power of conventional engine (kW) 260Weight of drivetrain and fluids in dieselbus (kg)
491
Net additional weight for battery electricbus (BEB) versus diesel bus (kg)
1477
Loss of passenger capacity for BEB versusdiesel bus (%)
35.1
Table: Input parameters [23]
Curb weight is 13,800 kg and transport weight is 4,200 kg.With 987 Wh/kg, BEB is successfully driven without any weight penalties.
Go to
Hiteshkumar Amipara TCO March 5, 2019 16 / 61
Methodology Deterministic TCO analysis
Effect of additional storage weight on transport capacity
Figure: Workflow of the correction factor
The available mass of transport capacity has beencalculated in terms of correction factor:
C =Mcapacity
Mcapacity −Mstorage(5)
where,
C: correction factor
Mcapacity: total transport capacity in kg
Mstorage: total storage weight in kg
Hiteshkumar Amipara TCO March 5, 2019 17 / 61
Methodology Validation
Validation of TCO analysis:Passenger Car
Figure: Validation [21]
Go to
Hiteshkumar Amipara TCO March 5, 2019 18 / 61
Methodology Stochastic TCO analysis
Stochastic TCO analysis
Figure: Workflow of the stochastic analysis
Vehicles Unit Stochastic inputparameters
ICEV e/L Diesel price
BEVe/kWh Electricity pricee/kWh Battery pack cost
FCEVe/kW Fuel cell system coste/kWh Hydrogen storage coste/kg Hydrogen price
ICEV, BEV,and FCEV
km Daily range
Table: Stochastic parameters
Non-Stochastic inputparameters
Annual fixed cost Vehicle tax, Insurance costAnnual running cost Maintenance & repair, Tire
cost, Driver wage
Table: Non-Stochastic parameters
Go to
Hiteshkumar Amipara TCO March 5, 2019 19 / 61
Results
Table of Contents
1 IntroductionMotivationThesis Contribution
2 MethodologyTCO calculation structureVehicle drivetrains and segmentsDeterministic TCO analysisValidationStochastic TCO analysis
3 ResultsDeterministic TCOStochastic TCO
4 Conclusions and Future Work
5 References
Hiteshkumar Amipara TCO March 5, 2019 20 / 61
Results Deterministic TCO
Results:Deterministic TCO for Passenger car
Figure: Deterministic analysis for Passenger car
Hiteshkumar Amipara TCO March 5, 2019 21 / 61
Results Deterministic TCO
Results:Deterministic TCO for Local bus
Figure: Deterministic analysis for Local bus
Internal combustion engine bus (ICEB), Battery electric bus (BEB), Fuel cellelectric bus (FCEB)
Hiteshkumar Amipara TCO March 5, 2019 22 / 61
Results Deterministic TCO
Results:Deterministic TCO for Light-duty vehicle
Figure: Deterministic analysis for LDV
CLDV (Conventional LDV), BLDV (Battery electric LDV), FLDV (Fuel cellelectric LDV).
Hiteshkumar Amipara TCO March 5, 2019 23 / 61
Results Deterministic TCO
Results:Deterministic TCO for Medium duty vehicle andHeavy-duty vehicle
Figure: Deterministic analysis for MDV
CMDV (Conventional MDV), BMDV(Battery electric MDV), FMDV (Fuelcell electric MDV)
Figure: Deterministic analysis for HDV
CHDV (Conventional HDV), BHDV(Battery electric HDV), FHDV (Fuelcell electric HDV)
Hiteshkumar Amipara TCO March 5, 2019 24 / 61
Results Deterministic TCO
Results:Deterministic TCO for Material handling vehicle(Class-1 & 2)
Figure: Deterministic analysis for MHV (Class-1) Figure: Deterministic analysis for MHV (Class-2)
BMHV (Battery electric MHV), FMHV (Fuel cell electric MHV).
Hiteshkumar Amipara TCO March 5, 2019 25 / 61
Results Deterministic TCO
Results: Deterministic TCO for Material handling vehicle(Class-3)
Figure: Deterministic analysis for MHV [Class-3]
MHV (Class-3) has the lower TCO than MHV (Class-1 and 2), reflecting bothlower CAPEX for the lift truck and power pack.
Hiteshkumar Amipara TCO March 5, 2019 26 / 61
Results Stochastic TCO
Results: Stochastic TCO for Passenger Car
Figure: Stochastic analysis for Passenger car
Hiteshkumar Amipara TCO March 5, 2019 27 / 61
Results Stochastic TCO
Results: Stochastic TCO for Local bus
Figure: Stochastic analysis for Local bus
Hiteshkumar Amipara TCO March 5, 2019 28 / 61
Results Stochastic TCO
Results: Stochastic TCO for Light-duty vehicle
Figure: Stochastic analysis for Light-duty vehicle
Hiteshkumar Amipara TCO March 5, 2019 29 / 61
Results Stochastic TCO
Results:Stochastic TCO for Medium duty vehicle andHeavy-duty vehicle
Figure: Stochastic analysis for Medium duty vehicle
FMDV and CMDV havealmost the same results by2030.
BHDV is likely to be thetechnology with the highestTCO.
Figure: Stochastic analysis for Heavy-duty vehicle
Hiteshkumar Amipara TCO March 5, 2019 30 / 61
Results Stochastic TCO
Results:Stochastic TCO for Material handling vehicle(Class-1 & 2)
Figure: Stochastic analysis for MHV (class-1)
Fuel cell MHV (Class-1,2) islikely to have a lower meanTCO.
Battery electric MHV has thelower CAPEX and fuel cost.
Figure: Stochastic analysis for MHV (class-2)
Hiteshkumar Amipara TCO March 5, 2019 31 / 61
Results Stochastic TCO
Results: Stochastic TCO for MHV (Class-3)
Figure: Stochastic analysis for MHV (Class-3)
Hiteshkumar Amipara TCO March 5, 2019 32 / 61
Conclusions and Future Work
Table of Contents
1 IntroductionMotivationThesis Contribution
2 MethodologyTCO calculation structureVehicle drivetrains and segmentsDeterministic TCO analysisValidationStochastic TCO analysis
3 ResultsDeterministic TCOStochastic TCO
4 Conclusions and Future Work
5 References
Hiteshkumar Amipara TCO March 5, 2019 33 / 61
Conclusions and Future Work
Conclusions 1/3
For the Deterministic TCO analysis:
For passenger cars, the BEV shows the potential to become the cost-competitivetechnology after 2020.
For local buses, the BEB and FCEB are likely to remain as the cost inefficienttechnologies.
For road freight vehicles, the market potential for conventional vehicles in theLDV and HDV segment from 2020 to 2030 was identified. On the other hand,BMDV and CMDV have the almost same TCO for MDV segment by 2030.
In terms of equipment cost, FMHVs are more expensive than BMHVs butconsidering the multi-shift warehouse operations, FMHVs are comparable toBMHVs.
Hiteshkumar Amipara TCO March 5, 2019 34 / 61
Conclusions and Future Work
Conclusions 2/3
For the Stochastic TCO analysis:
For passenger cars, BEV is the least expensive drivetrain after 2020, while theFCEV is likely to become cost-competitive after 2025.
For local buses, LDVs, and MDVs, the conventional vehicle has the lowest meanTCO.
The HDV segment is likely to have FCEV as the technology with the lowestTCO indicated by the mean TCO.
For MHVs (Class-1,2, and 3), the FMHV has the lowest mean and minimumvalue in comparison to BMHV.
Hiteshkumar Amipara TCO March 5, 2019 35 / 61
Conclusions and Future Work
Conclusions 3/3
The cost-competitiveness of the BEV is strongly linked with the assumed fuelprices for electricity, assumed battery pack cost as well as the specific energydensity of battery pack.
The comparative cost efficiency of the FCEV is strongly connected with theassumed fuel prices for hydrogen as well as the assumed fuel cell system cost.
BEVs are expected to be more economical at lower ranges and lower utilizationrates, whereas FCEVs provide very promising economic performance in case ofhigh range and high utilization of the vehicle.
Hiteshkumar Amipara TCO March 5, 2019 36 / 61
Conclusions and Future Work
Future Work
Include external costs such as climate external costs (greenhouse gas emissions)and Health external costs (air quality and noise).
Include Government subsidies.
Hiteshkumar Amipara TCO March 5, 2019 37 / 61
Conclusions and Future Work
CO2 emission calculation for Passenger Car and Bus
Calculates annual CO2 emission asspecified in the below equation [6]:
Ec = Ee (6)
where
Ec: CO2 emission in g CO2/a
E: Energy consumption in kWh/a
e: emission factor in g CO2/kWh
Car Fuel consumption[kWh/a]
CO2 emissionfactor[g CO2/kWh]
ICEV 12,838 239BEV 5,636 -FCEV 7,616 -
Table: CO2 emission factor and fuel consumption forCar [6]
Bus Fuel consumption[kWh/a]
CO2 emissionfactor[g CO2/kWh]
ICEB 264,384 239BEB 99,144 -FCEB 185,068 -
Table: CO2 emission factor and fuel consumption forBus
Annual CO2 emission for a ICEV is around 3.068 t CO2/a (112.806 g CO2/km).
Annual CO2 emission for a ICEB is around 63 t CO2/a (956 g CO2/km).
Hiteshkumar Amipara TCO March 5, 2019 38 / 61
References
Table of Contents
1 IntroductionMotivationThesis Contribution
2 MethodologyTCO calculation structureVehicle drivetrains and segmentsDeterministic TCO analysisValidationStochastic TCO analysis
3 ResultsDeterministic TCOStochastic TCO
4 Conclusions and Future Work
5 References
Hiteshkumar Amipara TCO March 5, 2019 39 / 61
References
F Bergk, W Knorr, and U Lambrecht
Climate Protection in Transport–Need forAction in the Wake of the Paris Climate Agreement.
Climate Change Mitigationin Transport until 2050 (2017).
Letmathe, P. and M. Suares
A consumer-oriented total cost of ownership model for different vehicle types in Germany.
Transportation Research Part D: Transport and Environment, 2017.
Kleiner, F. and H.E. Friedrich
Scenario analyses for the techno-economical evaluation of the market diffusion of future commercial vehicleconcepts.
2017.
Wu, G., A. Inderbitzin, and C. Bening
Total cost of ownership of electric vehicles compared to conventional vehicles: A probabilistic analysis andprojection across market segments.
Energy Policy, 2015.
Den Boer, Eelco and Aarnink, S and Kleiner, F and Pagenkopf, J
Zero emissions trucks: An overview of state-of-the-art technologies and their potential.
2013.
Bubeck, Steffen and Tomaschek, Jan and Fahl, Ulrich
Perspectives of electric mobility: Total cost of ownership of electric vehicles in Germany.
Transport Policy,2016.
Moultak, Marissa and Lutsey, Nic and Hall, Dale
Transitioning to zero-emission heavy-duty freight vehicles.
2017.
Hiteshkumar Amipara TCO March 5, 2019 39 / 61
References
Gnann, T and Wietschel, M and Kuhn, A and Thielmann, A and Sauer, A and Plotz, P and Moll, C and
Stutz, S and Schellert, M and Rudiger, D and others
Brennstoffzellen-Lkw: kritische Entwicklungshemmnisse, Forschungsbedarf und Marktpotential.
Wissenschaftliche Beratung des BMVI zur Mobilitats-und Kraftstoffstrategie. 2017.
James, Brian
2018 Cost Projections of PEM Fuel Cell Systems for Automobiles and Medium-Duty Vehicles Question andAnswer Motivation and Outline.
2018.
https://www.now-gmbh.de/en/national-innovation-programme/projektfinder/verkehr/
autostack-industrie.
Drive, US
Target explanation document: onboard hydrogen storage for light-duty fuel cell vehicles.
Department of Energy,2015.
Ramsden, Todd
Evaluation of the Total Cost of Ownership of Fuel Cell-Powered Material Handling Equipment.
2013.
Reid - Marketing Specialist, Catharine
FUEL CELL ELECTRIC BUSES: AN ATTRACTIVE VALUE PROPOSITION FOR ZERO-EMISSIONBUSES IN THE UNITED KINGDOM.
2016.
Stapelbroek, D.-I.M.
BT 2019 Stapelbroek FEV Battery trends.
2019.
Hiteshkumar Amipara TCO March 5, 2019 39 / 61
References
Ammermann, Heiko and Ruf, Yvonne and Lange, Simon and Fundulea, Dragos and Martin, Andre
Fuel Cell Electric Buses–Potential for Sustainable Public Transport in Europe A Study for the Fuel Cells andHydrogen Joint Undertaking, Roland Berger GmbH, Munchen, Germany, 2015, 52 p.
2016.
R. Micheli M.Sc.,Lehrstuhl fml Dipl.-Ing. M. Hanke, Linde Material Handling AG
Einsatz einer wasserstoffberiebenen Flurforderzeugflotte unter Produktionsbedingungen: Herausforderungen,Wirtschaftlichkeit, Nachhaltigkeit.
2015.
Dexheimer, Verena
Hedonic methods of price measurement for used cars.
Statistisches Bundesamt (Destatis), zuletzt abgerufen am, 2003.
Mathieu, Lucien
Marketplace, economic, technology, environmental and policy perspectives for fully electric buses in the EU.
2018.
Goehlich, D and Spangenberg, F and Kunith, A
Stochastic total cost of ownership forecasting for innovative urban transport systems.
838–842,2013.
Cerniauskas, Simonas and Grube, Thomas and Robinius, Martin and Stolten, Detlef
Hydrogen Supply Chain Costs for Different Geographical Distribution and Technology Penetration Scenarios.
2018.
Propfe, Bernd and Redelbach, Martin and Santini, Danilo and Friedrich, Horst
Cost analysis of plug-in hybrid electric vehicles including maintenance & repair costs and resale values.
World Electric Vehicle Journal,2012.
Hiteshkumar Amipara TCO March 5, 2019 39 / 61
References
Meeus, Marcel Meeus -Emiri, Marcel
Overview of Battery Cell Technologies Overview of battery technologies Bridging the Innovation Gap.
2018.
Karlsson, Elin
Charging infrastructure forelectric city buses: An analysis of grid impact and costs.
2016.
Loogen, F.
Nullemissions-nutzfahrzeuge Vom okologischen HoffnungstrA¤ger zur okonomischen Alternative.
2017.
CO2 emissions Target in Germany.
2017.
Plotz, Patrick and Gnann, Till and Wietschel, Martin
Total ownership cost projection for the German electric vehicle market with implications for its future powerand electricity demand.
2012.
Hiteshkumar Amipara TCO March 5, 2019 40 / 61
References
Thank You!
Hiteshkumar Amipara TCO March 5, 2019 40 / 61
References
Back-Up Slides
Hiteshkumar Amipara TCO March 5, 2019 41 / 61
References
Vehicle usage and TCO calculation
Vehicle usage and input parameters
Car Bus LDV MDV HDVMean dailymileage [km]
100 243 88 225 430
Vehicle lifetime[years]
10 10 10 10 10
MHV (Class-1,2, and 3) ValueNumber of shifts per day 2Number of hours per shift(hours)
7.25
Annual working hours(hours)
2000
ValueDiscount rate (i) 8%Vehicle holding period(N)
10 years
Retail Price Equivalentfactor (RPE)
1.5
Working day 272
Hiteshkumar Amipara TCO March 5, 2019 42 / 61
References
Input parameters
Input parameters
LDV MDV HDV Bus CarEngine power [kW] (only for ICEVs) 100 150 350 260 110Electric motor [kW] (for BEVs andFCEVs)
100 150 350 150 100
Fuel cell [kW] (only for FCEVs) 100 150 300 100 115HVAC [kW] (only for FCEB andBEB)
- - - 28 -
Table: Characteristics of the reference vehicle
MHV(class-1)
MHV(class-2)
MHV(class-3)
Fuel cell power [kW] 10 8 2Electric motor [kW](for FCEVs)
8 6 2
Electric motor [kW](for BEVs)
10 10 5
Table: Characteristics of the reference vehicle
Hiteshkumar Amipara TCO March 5, 2019 43 / 61
References
Effect of storage weight on transport capacity
Figure: Workflow for the correction factor
Characteristics ValueICEV Power density of engine [W/kg] 650
Density of diesel fuel [kg/L] 0.83Tank weight [g/L] 200
BEVandFCEV
Energy density of battery pack [Wh/kg] 235
Power density of E-motor [kW/kg] 5Power density of fuel cell system [W/kg] 650Compressed 700 bar H2 storage [kg/100kg] 5.4
Table: Characteristics of drivetrains technologies [5][22]
The effect of storage weight on transport capacity is expressed by thefollowing equation (5):
C =Mcapacity
Mcapacity −Mstorage(7)
where,
C: correction factor
Mcapacity : Total transport capacity in kg
Mstorage: Storage weight in kg
Hiteshkumar Amipara TCO March 5, 2019 44 / 61
References
Additional weight effect of a battery electric versus fuel cellelectric drivetrain
Weight consideration analysis
Figure: Weight consideration analysis
Parameters ValueEnergy consumption for fuel cell electricbus at the wheels (kWh/km)
2.72
Mean Mileage (km) 243Weight of hydrogen storage (kg) 367Power of fuel cell system (kW) 100Power of electric motor for bus (kW) 150Weight of electric motor (kg) 30Total storage weight of fuel cell electricbus (kg)
732.25
Total storage weight of BEB (kg) 1968.8Net additional weight for BEB versus fuelcell electric bus (FCEB) (kg)
1235.7
Loss of passenger capacity for BEB versusFCEB (%)
29.42
Table: Input parameters [15]
The required energy density of the battery pack is 650 Wh/kg.
Hiteshkumar Amipara TCO March 5, 2019 45 / 61
References
Operating expenditures
Energy consumption (Linear regression analysis) for Road freight vehicle
Energy consumption
Hiteshkumar Amipara TCO March 5, 2019 46 / 61
References
Operating expenditures
Energy consumption for Car, Local Bus, and MHV
Figure: Energy consumption for car and local bus
Figure: Energy consumption for MHV
Figure: Additional efficiency gain per year
Hiteshkumar Amipara TCO March 5, 2019 47 / 61
References
Operating expenditures
Maintenance and repair cost
Figure: Maintenance and repair cost
Figure: Maintenance and repair cost for MHV
Hiteshkumar Amipara TCO March 5, 2019 48 / 61
References
Operating expenditures
Other Operating costs
Figure: Fixed operating cost parameters
Figure: Key operating parameters
Hiteshkumar Amipara TCO March 5, 2019 49 / 61
References
Validation for MDVsValidation
Input parameters Unit 2020Glider price for all threedrivetrains
e 40000
Hydrogen price e/kg 4.77Electricity price e/kWh 0.127Daily Range km 200Annual kilometretravelled
km 52000
Diesel price e/L 1.18Battery pack cost e/kWh 240Internal combustionengine cost
e/kW 60
Fuel cell system cost e/kW 190Hydrogen storage cost(700 bar)
e/kWh 18
Battery pack capacity kWh 230Holding period year 10Interest rate % 4
Table: Input parameters
Used different RPE
Bottom-up approach
Hiteshkumar Amipara TCO March 5, 2019 50 / 61
References
Validation for HDVs
Input parameters Unit 2020Glider price for allthree drivetrains
e 60000
Hydrogen price e/kg 4.77Electricity price e/kWh 0.112Daily Range km 1000Annual kilometretravelled
km 141,960
Diesel price e/L 1.18Battery pack cost e/kWh 240Fuel cell systemcost
e/kW 190
hydrogen storagecapacity (700 bar)
kWh 2570
Hydrogen storagecost (700 bar)
e/kWh 18
Battery packcapacity
kWh 152
Holding period year 8Interest rate % 4
Table: Input parameters
Used different RPE
Bottom-up approach
Hiteshkumar Amipara TCO March 5, 2019 51 / 61
References
Validation for Bus
Input parameters Unit 2018Base vehicle pricefor electric bus
e 247863
Base vehicle pricefor diesel bus
e 213675
Electricity price e/kWh 0.112Daily Range km 250Annual kilometretravelled
km 91250
Diesel price e/L 1.175Battery pack cost e/kWh 335Battery packcapacity
kWh 451
Holding period year 8Interest rate % 4
Table: Input parameters
Excluding external health cost
Bottom-up approach
Hiteshkumar Amipara TCO March 5, 2019 52 / 61
References
Stochastic analysis: Stochastic cost variablesStochastic analysis: stochastic parameters
Figure: Stochastic analysis of Hydrogen storage cost
Figure: Stochastic analysis of Fuel cell system cost
Hiteshkumar Amipara TCO March 5, 2019 53 / 61
References
Stochastic analysis: Battery pack cost
Cost will decrease over the years
SD will decrease
2020 2025 2030- 84 75291.118 165.35 151.67259.92 191.32 136.28240 200 161401.33 293.67 186404 332 260155 105 90163.02 139.08 -182.4 145.92 -217.74 136.8 91.2361.38 96.9 57209.76 151.62 -173.28 - -182.4 - -148.2 - -
Table: Input parameters
Hiteshkumar Amipara TCO March 5, 2019 54 / 61
References
Stochastic analysis: Electricity price
Input parameters yearElectricity price(e/kWh)
2020 0.163 0.213 0.216 0.24 0.292
2025 0.182 0.216 0.239 0.252 0.3122030 0.19 0.222 0.250 0.265 0.284
Table: Input parameters
Hiteshkumar Amipara TCO March 5, 2019 55 / 61
References
Stochastic analysis: Diesel price
Input parameters yearDiesel price (e/L) 2020 1.163 1.37 1.788 1.792 1.59
2025 1.346 1.635 1.863 1.979 1.682030 1.53 1.90 2.106 2.185 1.78
Table: Input parameters
Hiteshkumar Amipara TCO March 5, 2019 56 / 61
References
Stochastic analysis: Hydrogen price
Input parameters yearHydrogen price(e/kg)
2020 8.29 7.95 12.62 11.012 10.3323
2025 6.69 7.3 11.309 9.47 10.362030 5.09 6.65 10.65 7.9458 10.36
Table: Input parameters
Hiteshkumar Amipara TCO March 5, 2019 57 / 61
References
Stochastic analysis: Daily mean range
Vehicles Unit Bus Car LDV MDV HDVMinimum daily range (assumed 25 % of trip) km 206 24 22 80 251Mean daily range km 243 100 88 225 430Maximum daily range (assumed 95 % trip forcar and 90 % trip for remaining vehicles)
km 329 368 209 499 724
Average annual range km 66,096 27,200 23,936 61,200 116,960
Table: Input parameters
Hiteshkumar Amipara TCO March 5, 2019 58 / 61
References
Initial purchasing price (IPP) calculation structure forBattery electric powertrain
IPP structure for all three drivetrains
Powertrain
cost (€)
Chassis and
Body cost (€)
Production
cost (€)
Retail price
equivalent
factor
Initial
Purchasing
Price (€)
Energy consumption
(kWh/km), Battery
pack efficiency, DOD
Battery pack
storage cost (€)
Electric motor cost (€)
Daily mileage
(km)
Battery pack capacity
(kWh) X cost per kWh
Hiteshkumar Amipara TCO March 5, 2019 59 / 61
References
Initial purchasing price (IPP) calculation structure for Fuelcell electric powertrain
Powertrain
cost (€)
Chassis and
Body cost (€)
Production
cost (€)
Retail price
equivalent
factor
Initial
Purchasing
Price (€)
Energy consumption
(kg/km), Fuel cell
system efficiency
Hydrogen
storage cost (€)
Electric motor cost (€),
Fuel cell system cost (€),
Battery pack cost (€)
Daily mileage
(km)
Hydrogen storage
capacity (kg) X cost per
kg
Hiteshkumar Amipara TCO March 5, 2019 60 / 61
References
Initial purchasing price (IPP) calculation structure forConventional powertrain
Powertrain
cost (€)
Chassis and
Body cost (€)
Production
cost (€)
Retail price
equivalent
factor
Initial
Purchasing
Price (€)
Energy consumption
(L/km), Engine
efficiency
Storage cost
(€)
Engine cost (€)
Daily mileage
(km)
Hiteshkumar Amipara TCO March 5, 2019 61 / 61