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Fuel cell hybrid electric trucks have become a cutting-edge field in understanding urban traffic emissions due to their enormous potential in low-carbon areas. In order to improve the economy of fuel cell hybrid electric trucks and reduce the decline of fuel cell lifespan, this paper proposes a multi-objective energy management strategy that optimizes weight coefficients. On the basis of establishing a fuel cell battery hybrid system model, three modes of uniform speed, acceleration, and deceleration were identified through clustering analysis of vehicle speed. Reinforcement learning algorithms were used to learn the corresponding weights for different modes, which reduced the decline in fuel cell life while improving the economic efficiency. The simulation results indicate that, under the conditions of no load, half load, and full load, the truck only sacrificed 0.9–5.6%, 1.7–2.6%, and 1.2–1.6% SOC, saving 5.7–6.45%, 5.9–6.67%, and 6.1–6.67% in lifespan loss, and reducing hydrogen consumption by 3.0–7.1%, 2.8–4.4%, and 1.0–3.0%, respectively. [ABSTRACT FROM AUTHOR]

The road freight sector faces significant challenges in decarbonisation, driven by high energy demand and limited availability of low-emission fuels and commercialised zero-emission vehicles. This study investigates intangible costs associated with advanced electric and hydrogen-powered trucks, including recharging/refuelling time, cargo capacity limitations, and buyer reluctance towards emerging technologies. Utilising a comprehensive whole-systems modelling approach considering low- and zero-emission fuels, inter-sectoral dynamics, and the carbon budget, we explore cost-optimal decarbonisation pathways for heavy, medium, and light trucks. Scenario and sensitivity analyses reveal the following insights: (1) Electric trucks dominate the market under mitigation pathways across all weight categories. However, the inclusion of intangible costs triggers a shift, leading to the emergence of hydrogen fuel cell vehicles for heavy trucks, while battery electric vehicles are preferred for medium and small trucks. (2) Prioritising heavy truck decarbonisation and taking early action are crucial to avoid carbon lock-in effects. (3) Considering limited decarbonisation options, where electric and hydrogen-fuelled trucks are pivotal, this research highlights the significance of policy instruments targeting operational expenditures over conventional purchase price incentives. Such policies offer dual benefits by supporting truck owners and directing incentives more precisely towards achieving measurable emission reductions. [ABSTRACT FROM AUTHOR]

Road freight transport on hilly routes represents a significant challenge for the advancement of fuel cell electric trucks because of the high-performance requirements for fuel consumption, vehicle lifetime, and battery charge control. Therefore, it is essential to optimize the vehicle design and energy management, which greatly influence the driving performance and total cost of ownership. This paper focuses on the cost-optimal design and energy management of fuel cell electric trucks, considering five key influencing factors: powertrain component sizing, driving cycle, vehicle weight, component degradation, and market prices. The cost optimization relies on a novel predictive energy management scheme based on dynamic programming and the systematic calibration of control parameters. The paper analyzes the simulation results to highlight three main findings for fuel cell electric trucks: 1) cost-optimal energy management is essential to define the best trade-off between fuel consumption and component degradation; 2) the total cost of ownership is significantly influenced by component sizing, driving cycles, vehicle weight, and market prices; 3) predictive energy management is highly beneficial in challenging road topographies for substantial cost-saving and lower component size requirements. [Display omitted] • Investigation on total cost of ownership of heavy-duty fuel cell electric vehicles. • Optimal vehicle design and control in demanding routes for performance requirements. • Energy management optimization for minimum ownership cost in realistic driving scenarios. • Trade-off analysis between fuel consumption and expected powertrain components life. • Significant benefits of predictive energy management in challenging road topographies. [ABSTRACT FROM AUTHOR]

The effect of hydrogen fuel cell heavy-duty trucks (HHDTs) on traffic decarbonization throughout the life cycle has barely been investigated, particularly in the China context. Neither current hydrogen production structure and potential innovations, nor the HHDT manufacturing processes have been considered in any studies. Therefore, we initiated a novel life cycle assessment (LCA) on the energy and greenhouse gas (GHG) emissions of HHDTs concerning the actual hydrogen production in China, and then we evaluated the effect of policy impact on emission of heavy-duty trucks (HDTs) under policy-dependent scenarios with a more comprehensive range of factors, such as the structure integrity of future HDTs, that few have included. Results show that the life cycle GHG emissions of HHDTs under current hydrogen production technology and supply chain system are 44.0 % and 27.0 % higher than that of diesel-powered heavy-duty trucks (DHDTs) and battery electric heavy-duty trucks (BHDTs), while energy consumptions are 34.9 % and 36.5 % higher, respectively. However, the results indicate that carbon emission decline rate of HHDTs over their 2020 emissions become more favorable with that of BHDTs and DHDTs, under both future scenarios of 2030, 2040 and 2050. This study can provide a scientific basis for intensifying GHG emission reduction in HDTs. • We conducted LCA comparison of energy consumption and GHG emissions of different fuel type heavy-duty vehicles. • Actual hydrogen production structure and potential innovations in China was considered. • Scenarios were designed to evaluate the reduction potentials in long-term perspective. • Currently, the energy saving and carbon reduction effect of hydrogen fuel cell heavy-duty trucks could not be strong. [ABSTRACT FROM AUTHOR]

[Display omitted] • The proposed model combines renewable-based fuel cycle and vehicle cycle. • Five heavy-duty vehicle decarbonization pathways are compared. • The impacts of gross vehicle weight and vehicle range are explored. • Battery electric trucks offer a 7 % lower ton-km cost than diesel trucks. • Fuel cell electric trucks become more cost-effective at ranges over 1100 km. Decarbonizing heavy-duty vehicles is becoming increasingly important, yet multiple renewable-based decarbonization pathways have not been compared systematically. To fill this gap, this study develops a techno-economic and environmental model that integrates the fuel cycle and vehicle cycle to assess these pathways for China. The model includes two energy storage technologies: batteries and hydrogen, three energy transmission options, and two vehicle types: fuel cell electric vehicles and battery electric vehicles. Five distinct low-carbon pathways are evaluated on a ton-kilometer basis, including cost, greenhouse gas emissions, and abatement cost relative to conventional diesel trucks. Results indicate that the most cost-effective battery electric vehicle pathway offers a 7 % lower ton-km cost than diesel trucks for a 49-ton gross vehicle weight. Battery electric vehicle charging combined with hydrogen for power generation is more cost-effective than direct use of hydrogen in fuel cell electric vehicles. All studied pathways can achieve over 80 % emission reduction compared to diesel trucks, with fuel cell electric vehicle pathways having the highest abatement costs of 103–117 USD/tonCO 2. Analysis of the impact of gross vehicle weight and vehicle range indicates that battery electric vehicle pathways outperform fuel cell electric vehicle pathways across most dimensions. Costs of battery electric vehicle pathways do increase sharply for vehicle ranges beyond about 700 km, and fuel cell electric vehicles become more cost-effective relative to battery electric vehicles for ranges above approximately 1100 km, although all pathways are much more costly than diesel trucks at long ranges. The sensitivity analysis highlights the importance of powertrain efficiency and cost projections show that fuel cell electric heavy-duty vehicles can achieve cost-parity before 2030. These results highlight the desirability of promoting the adoption of heavier battery electric vehicles and providing more targeted subsidies for long-range fuel cell electric vehicles. [ABSTRACT FROM AUTHOR]

Electric powertrains in terms of battery electric vehicles (BEV) are considered to be very interesting for heavy truck transportations. The challenge is the need for very large onboard energy and batteries. Long-term fuel cells (FCs) are considered an interesting support system for heavy-duty BEV, but in the short term, a range extender (REX) is also interesting. A heavy-duty BEV with 970 kWh batteries installed can handle 27% of all possible missions for the Scania fleet considering daily recharging. The back-up range extender (BUREX) can expand this figure to 55% utilized 20 days per year. If a customer has a few very energy-demanding use cases each year and does not want to pay for all the batteries needed, the BUREX may be an especially good option. The BUREX reduces life-cycle CO2 emissions, irrespective of the generation mix of the grid supplying the electricity used in vehicle manufacturing and battery charging. The BUREX reuse of the existing electric components of the BEV powertrain enables the installation of a 10% larger battery pack while being 80% less costly. The BUREX also adds redundancy to the BEV concept while recharging infrastructure improves, especially in rural places. These results indicate that the BUREX concept is a powerful short-term solution that could enable greater use of HD FC and BEV trucks while charging infrastructure and FC technologies gradually become more mature. [ABSTRACT FROM AUTHOR]

This paper proposes a cost-effective way to design and operate fuel cell hybrid electric trucks (FCHETs) where a chance-constrained optimization is formulated. The aim of the introduced problem is to minimize a summation of component cost and operational cost with consideration of fuel cell (FC) degradation and cycle life of energy buffer. We propose to decompose the problem into two sub-problems that are solved by sequential convex programming. The delivered power satisfies a cumulative distribution function of the wheel power demand, while the truck can still traverse driving cycles with a similar speed and travel time without delivering unnecessarily high power. This allows to downsize powertrain components, including electric machine, FC and energy buffer. A case study considering different energy buffer technologies, including supercapacitor (SC), lithium-ion battery (LiB), and lithium-ion capacitor (LiC) is investigated in a set of trucking applications, i.e. urban delivery, regional delivery, construction, and long-haul. Results show that the power rating of the electric machine is drastically reduced when the delivered power is satisfied in a probabilistic sense. Moreover, the configuration with LiB as the energy buffer has the lowest expense but the truck with LiC can carry more payload. [ABSTRACT FROM AUTHOR]

Energy management strategies have a significant impact on the hydrogen economy of fuel cell trucks and the lifetime of battery and fuel cell systems. This contribution presents the design and optimal calibration of an energy management strategy that is adaptive to the battery and ambient temperatures. Indeed, fuel cell trucks face critical operating conditions due to high ambient temperatures or high loads on long uphill roads. However, the presented adaptive energy management strategy shifts the electric loads to the fuel cell system to limit the battery usage, avoiding accelerated degradation due to battery temperature peaks without hindering the hydrogen economy. The strategy design and calibration involves a multi-objective optimization of performance indicators related to hydrogen consumption, fuel cell degradation, battery thermal state, equivalent charge/discharge cycles, and charge control. This work uses AVL CAMEO to systematically vary the adaptive curve parameters to explore the trade-off between the key performance indicators. The calibration considers real-world driving cycles of road freight vehicles, including measured speed, road elevation, and variable vehicle mass. Moreover, the energy management design is robust because the performance indicators are evaluated over 8935 km, covering an extensive range of real-world driving scenarios. Eventually, the adaptive and predictive energy management strategy proposed in this work can meet all the performance targets thanks to the optimal calibration, and it is particularly effective in avoiding battery temperature peaks. [ABSTRACT FROM AUTHOR]

Fuel cell-battery hybrid systems for the powertrain, which have the advantage of emission-free power generation and adapt to material transport and emission reduction, are investigated. Based on the characteristics of the fuel cell system and the characteristics of the electric forklift truck powertrain system, this work defines the design principle of the control strategy to improve overall performance and economy. A simulation platform for fuel cell and electric vehicles has been established. The optimal performance of the fuel cell stack and the battery capacity were defined for the specific application. An energy control strategy was defined for different operating cycles and operating conditions. Model validation involved comparing simulation results with experimental data obtained during VDI60 test protocol. The main parameters that influence the forklift performance were defined and evaluated, such as energy loss, fuel cell operating conditions and different battery charging cycles. The optimal size of the fuel cell stack of 11 kW and the battery of 10 Ah was determined for the specific load profile with the proposed control strategy. The results obtained in this work forms the basis for an in-depth study of the energy management of fuel cell battery drive trains for forklift trucks. • Lift truck simulation model with hybrid power pack is developed. • PEMFC-Battery hybrid model for lift truck application was analyzed. • Real lift truck load cycle was simulated. • Balance of plant optimization and control strategy was done. [ABSTRACT FROM AUTHOR]

This study explored the national hydrogen refueling infrastructure requirement along major United States (US) interstate highway corridors to support the deployment of fuel cell electric trucks (FCETs) for the national long-haul trucking fleet. Given the long-haul trucking shipment demand in 2025 projected by the Freight Analysis Framework, locations and capacities of hydrogen stations were identified for inter-zone freight flows, and the total daily refueling demand was estimated for intra-zone flows for each FAF zone. Based on the infrastructure deployment results, we conducted an economic feasibility analysis of FCETs by evaluating the total ownership cost. We found that when the FCET penetration is relatively high (e.g., 10% penetration), FCETs become more competitive in terms of fuel cost and idling cost and could be economic viable if the incremental vehicle cost is reduced to meet the near-term FCET technology cost targets and the liquefaction cost is reduced to an optimal case. We also observed that the station cost depends on regional factors, particularly regional demand, which is used to determine station capacity. Thus, one possible strategy for station roll-out is to have early investment in target regions where station costs are expected to be relatively low such as the Pacific and West South Central regions. [ABSTRACT FROM AUTHOR]

This study provides a comprehensive and up-to-date life-cycle comparison of hydrogen fuel cell electric trucks (FCETs) and their conventional diesel counterparts in terms of energy use and air emissions, based on the ensemble of well-established methods, high-fidelity vehicle dynamic simulations, and real-world vehicle test data. For the centralized steam methane reforming (SMR) pathway, hydrogen FCETs reduce life-cycle or well-to-wheel (WTW) petroleum energy use by more than 98% compared to their diesel counterparts. The reduction in WTW air emissions for gaseous hydrogen (G.H2) FCETs ranges from 20 to 45% for greenhouse gases, 37–65% for VOC, 49–77% for CO, 62–83% for NOx, 19–43% for PM10, and 27–44% for PM2.5, depending on vehicle weight classes and truck types. With the current U.S. average electricity generation mix, FCETs tend to create more WTW SOx emissions than their diesel counterparts, mainly because of the upstream emissions related to electricity use for hydrogen compression/liquefaction. Compared to G.H2, liquid hydrogen (L.H2) FCETs generally provide smaller WTW emissions reductions. For both G.H2 and L.H2 pathways for FCETs, because of electricity consumption for compression and liquefaction, spatio-temporal variations of electricity generation can affect the WTW results. FCETs retain the WTW emission reduction benefits, even when considering aggressive diesel engine efficiency improvement. [ABSTRACT FROM AUTHOR]

• Methodology for life cycle GHG emission reduction potential of battery electric trucks. • Operational range coverage analysis for large-scale battery electric trucks adoption. • Different electrification scenarios for battery and charging technology improvement. • Decarbonization of electricity generation for battery charging and battery production. • Complementary solution of renewable fuels in achieving the zero GHG emission target. Large-scale adoption of battery electric trucks (BETs) might be a practical solution for reducing the greenhouse gas (GHG) emission in road freight transport sector if certain requirements are met. The minimum requirements are: 1) to overcome the operational range restrictions of BETs, and 2) to access an electricity power network with a certain level of emission intensity for the battery charging and battery production. In this study, we use a parametric GHG emission life cycle analysis (LCA) combined with a BET operational range coverage analysis to develop a methodology to provide a realistic estimation of BET's large-scale adoption and its GHG emission reduction potential for different electrification scenarios for battery and charging technology improvements in trucks with gross vehicle weight (GVW) over 3.5 tons in Finland and Switzerland. Life cycle (LC) GHG emission reduction potential in Finland is estimated to be very low (around 30% with the help of electric road system (ERS) in some routes and around 12% without ERS) in the short-term electrification scenarios; however, the mid-term and long-term scenarios are promising for LC GHG emission reduction potentials (up to 60%) even with the current level of electricity emission factors in Finland. In Switzerland, LC GHG emission reduction potential is estimated to be quite high (74% in Switzerland vs. 12%-30% in Finland) compared to Finland in the short-term electrification scenarios; however, the midterm and long-term scenarios show high LC GHG emission reduction potentials for Switzerland (around 93%), while Finland needs the help of full-decarbonization of electricity generation for battery charging and battery production in BETs, and use of renewable fuels in other trucks, to achieve high emission reduction. [ABSTRACT FROM AUTHOR]