Publications

The thermal management system and the balance-of-plant (BoP) in fuel cell electric vehicles (FCEV) are characterized by a particularly high level of complexity and a number of interfaces. Optimizing the efficiency of the overall vehicle is of special importance to maximize the range and increase the attractiveness of this technology to customers. This paper focuses on the optimization potential of the air supply system in the BoP whereby the charging concepts of the electric supercharger (ESC) and the electrically assisted turbocharger (EAT) as well as the integration of water spray injection (WSI) at the compressor inlet are investigated in the framework of an FCEV complete vehicle co-simulation. As a benchmark for the integration of these optimization measures the complete vehicle co-simulation is designed for a fuel cell electric passenger car of the current generation. Here thermo-hydraulic fluid circuits in the thermal management software KULI are coupled with mathematical-physical models in MATLAB/Simulink. Applying advanced simulation methodologies for the components of fuel cell powertrain and vehicle cabin enables the mapping of the effects of realistic operating conditions on the FCEV characteristics. The EAT offers the advantage over the ESC that due to the arrangement of an exhaust gas turbine a part of the exhaust gas enthalpy flow downstream of the fuel cell stack can be recovered which reduces the electrical compressor drive power. Moreover an additional reduction of this power consumption can be achieved by WSI as the effect of evaporative cooling lowers the initial compression temperature. For analysis and comparison these concepts are again modeled with high degree of detail and integrated into the benchmark overall vehicle simulation. The results indicate considerable reductions in the electric compressor drive power of the EAT compared to the ESC with noteworthy potential for reducing the vehicle’s hydrogen consumption. At an operating point in Worldwide harmonized Light Duty Test Cycle (WLTC) under 35 ◦ C ambient temperature and 25 % relative humidity the electrical compressor drive power shows a reduction potential of −40 % which corresponds to a vehicle-level hydrogen consumption reduction of up to −3 %. In addition the results also highlight the effect of the WSI in both charging concepts whereby its potential to reduce the hydrogen consumption on the overall vehicle level is relatively small. In WLTC at 35 ◦C ambient temperature and 25 % relative humidity the compressor drive power reduction potential for ESC and EAT averages −5 % while the effect on hydrogen consumption is only around −0.25 %.

Clean hydrogen (H2) is highly desirable for the sustainable development of society in the era of carbon neutrality. However the current capability of water electrolysis and steam methane (CH4) reforming to produce green and blue H2 is very limited mainly due to the high production cost difficult scale-up technology or operational risk. Here we propose the direct catalytic decomposition of diesel using a nano-Fe-based catalyst to produce the so-called ‘‘jadeite H2” while simultaneously fixing the carbon from the diesel in the form of carbon nanotubes (CNTs). Efforts are made to understand the suppression mechanism of the CH4 byproduct such as by tuning the catalyst type space velocity and reaction time. The optimal green index (GI)—that is the molar ratio of H2/carbon in a gaseous state—of the proposed technology exceeds 42 which is far higher than those of any previously reported chemical vapor deposition (CVD) method. Moreover the carbon footprint (CFP) of the proposed technology is far lower than those of grey H2 blue H2 and other dehydrogenation technologies. Compared with most of the technologies mentioned above the energy consumption (per mole of H2) and reactor amplification of the proposed technology validate its high efficiency and great practical feasibility.

As the global push for carbon neutrality accelerates energy efficiency has become essential for sustainable development especially for nations like Nigeria that face rising energy demands and significant environmental challenges. This study explores how integrating energy efficiency with carbon neutrality can support Nigeria’s strategic energy goals while offering global lessons for other countries facing similar challenges focusing on key sectors including industry transport and power generation. The study systematically examines the impacts of renewable energy (RE) technologies like solar wind and hydropower—alongside policy reforms technological innovations and demand-side management strategies to advance energy efficiency in Nigeria. Key findings include the identification of strategic policy frameworks technological solutions and the transformative role of green hydrogen in decarbonizing hard-to-electrify sectors. The study also emphasizes the importance of international climate finance decentralized RE systems like solar mini-grids for improving energy access and economic opportunities for job creation in the RE sector. Furthermore it highlights the need for behavioral changes community engagement and consistent policy implementation to address infrastructure gaps and drive energy efficiency goals. The novelty of this research lies in its scenario-based analysis of Nigeria’s low-carbon transition detailing both the opportunities and challenges such as policy inconsistencies infrastructure deficits and financial constraints. The findings stress the importance of international collaboration technological advancements and targeted investments to overcome these challenges. By offering actionable insights and strategic recommendations this study provides a roadmap for policymakers industry stakeholders and researchers to drive Nigeria towards a sustainable carbon-neutral future by 2050.

This paper presents QDQN-ThermoNet a novel Quantum-Driven Dual Deep Q-Network framework for intelligent thermal regulation in next-generation electric vehicles with hybrid energy systems. Our approach introduces a dual-agent architecture where a classical DQN governs solid-state battery thermal management while a quantumenhanced DQN regulates proton exchange membrane fuel cell dynamics both sharing a unified quantumenhanced experience replay buffer to facilitate cross-system information transfer. Hardware-in-the-Loop validation across diverse operational scenarios demonstrates significant performance improvements compared to classical methods including enhanced thermal stability (95.1 % vs. 82.3 %) faster thermal response (2.1 s vs. 4.7 s) reduced overheating events (0.3 vs. 3.2) and superior energy efficiency (22.4 % energy savings). The quantum-enhanced components deliver 38.7 % greater sample efficiency and maintain robust performance under sparse data conditions (33.9 % improvement) while material-adaptive control strategies leveraging MXeneenhanced phase change materials achieve a 50.3 % reduction in peak temperature rise during transients. Component lifetime analysis reveals a 33.2 % extension in battery service life through optimized thermal management. These results establish QDQN-ThermoNet as a significant advancement in AI-driven thermal management for future electric vehicle platforms effectively addressing the complex challenges of coordinating thermal regulation across divergent energy sources with different optimal operating temperatures.

In response to the growing global interest in hydrogen as an energy carrier this study provides the first attempt to develop a baseline inventory of U.S. hydrogen emissions from production distribution and storage. The scope of this study was limited to pure hydrogen emissions and excludes emissions from low purity hydrogen streams and carriers. A detailed literature search was conducted utilizing various greenhouse gas emissions inventory protocol principles and guidelines to consolidate a list of activity data and emission factors. The best available activity data and emission factors were then selected via a Multi-Criteria-Based Decision Making Method named Technique for Order Preference by Similarity to Ideal Solution or modelled using best-engineering estimates. The study estimated total U.S. hydrogen emissions of 0.063 MMTA with emission bounds ranging from 0.02 to 0.11 MMTA. Given the total estimated H2 production capacity of 7.97 MMTA the study estimates a total U.S. hydrogen emission rate for production distribution and storage of 0.79% (0.26%–1.32%). To reduce the uncertainty in the estimated total hydrogen emissions future work should be conducted to measure facility-level hydrogen emission factors across multiple sectors. The inventory framework developed in this study can serve as a living document that can be updated and enhanced as more empirical data is obtained. This study also provides detailed insights regarding key emission or leakage sources and causes from each supply chain stage. The insights and conclusions from this study can provide direction for hydrogen production companies and safety professionals as they develop hydrogen emission mitigation measures and controls.

This study investigates numerically combustion attributes and NOx formation of premixed ammonia-hydrogen/air flames within a swirl burner of a gas turbine considering various conditions of hydrogen fraction (HF: 0 % 5 % 30 % 40 % and 50 %) equivalence ratio (φ: 0.85 1.0 and 1.2) and mixture inlet temperature (Tin: 400–600 K). The results illustrate that flame temperature increases with hydrogen addition from 1958 K for pure ammonia to 2253 K at 50 % HF. Raising the inlet temperature from 400 K to 600 K markedly enhances combustion intensity resulting in an increase of the Damköhler number (Da) from 117 to 287. NOx levels rise from ∼1800 ppm (0 % HF) to ∼7500 ppm (50 % HF) and peak at 8243 ppm under lean conditions (φ = 0.85). Individual NO N2O and NO2 emissions also reach maxima at φ = 0.85 with values of 5870 ppm 2364 ppm and 10 ppm respectively decreasing significantly under richer conditions (2547 ppm 1245 ppm and 5 ppm at φ = 1.2). These results contribute to advancing low-carbon fuel technologies and highlight the viability of ammonia-hydrogen co-firing as a pathway toward sustainable gas turbine operation.

Green hydrogen is essential for advancing the energy transition as it is regarded as a CO2-neutral flexible and storable energy carrier. Particularly in steel production which is known for its high energy intensity hydrogen has great potential to replace conventional energy sources. In a game-theoretic bi-level optimization model involving a power plant operator and a steel company we investigate in which situations the production and use of green hydrogen is advantageous from an economic and ecological point of view. Through an extensive case study based on a realworld scenario we can observe that hydrogen production can serve as a profitable and flexible secondary income opportunity for the power plant operator and help avoid curtailment and spot market losses. On the other hand the steel manufacturer can reduce CO2 emissions and associated costs while also meeting the growing customer demand for low-carbon products. However our findings also highlight important trade-offs and uncertainties. While lower electricity generation costs or improved electrolyzer efficiency enhance hydrogen’s competitiveness increases in coal and CO2 emission prices do not always result in greater hydrogen adoption. This is due to the persistent reliance on a non-replaceable share of coal in steel production which raises the overall cost of both low-carbon and carbon-intensive steel. The model further shows that consumer demand elasticity plays a critical role in determining hydrogen uptake. These insights underscore the importance of not only reducing hydrogen costs but also designing supportive policies that address market acceptance and the full cost structure of green industrial products.

A comprehensive understanding of consumer preferences and demand factors is essential for successfully implementing demand-side strategies for alternative energy solutions such as hydrogen. This study aims to identify the key determinants influencing the adoption propensity for Hydrogen fuel cell vehicles (HFCVs) in the Kingdom of Saudi Arabia (KSA). Developing a conceptual framework to organise the key factors influencing consumers’ decisions to adopt or reject this technology. Using data from an online survey of 384 prospective customers we employed structural equation modelling (SEM) via Smart-PLS 4.1 to analyze consumer intent. The findings reveal that perceived benefits barriers opinions and governmental initiatives have a significant impact on the likelihood of HFCV adoption. The study emphasises the significance of collaborative efforts among key stakeholders including manufacturers hydrogen producers research institutions and financial entities in addressing challenges and advancing the development of the hydrogen transportation ecosystem in KSA. Financial incentives and subsidies such as purchasing subsidies awareness and reduced registration costs for HFCVs may be instituted.

With the growing significance of hydrogen in the global energy transition research on its pricing mechanisms has become increasingly crucial. Focusing on hydrogen markets predominantly supplied by electrolytic production this study proposes a nodal marginal hydrogen price decomposition algorithm that explicitly incorporates the time-delay dynamics inherent in hydrogen transmission. A four-dimensional price formation framework is established comprising the energy component network loss component congestion component and time-delay component. To address the nonconvex optimization challenges arising in the market-clearing model an improved second-order cone programming method is introduced. This method effectively reduces computational complexity through the reconstruction of time-coupled constraints and reformulation of the Weymouth equation. On this basis the analytical expression of the nodal marginal hydrogen price is rigorously derived elucidating how transmission dynamics influence each price component. Empirical studies using a modified Belgian 20-node system demonstrate that the proposed pricing mechanism dynamically adapts to load variations with hydrogen prices exhibiting a strong correlation with electricity cost fluctuations. The results validate the efficacy and superiority of the proposed approach in hydrogen energy market applications. This study provides a theoretical foundation for designing efficient and transparent pricing mechanisms in emerging hydrogen markets.

The operational optimization of industrial boilers utilizing hydrogen-enriched natural gas is constrained by two critical gaps: insufficient understanding of the coupled effects of hydrogen blending ratio equivalence ratio and boiler load on combustion performance— compounded by unresolved challenges of combustion instability flashback and elevated NOx emissions—and a lack of systematic investigations combining these parameters in industrial-scale systems (prior studies often focus on single variables like hydrogen fraction). To address this a comprehensive computational fluid dynamics (CFD) analysis was conducted on a 2.1 MW industrial boiler employing the Steady Laminar Flamelet Model (SLFM) with a modified k-ε turbulence model and the GRI-Mech 3.0 mechanism. Simulations covered hydrogen fractions (f(H2) = 0–25%) equivalence ratios (Φ = 0.8–1.2) and load conditions (15–100%). All NOx emissions reported herein are normalized to 3.5% O2 (mg/Nm3 ) for regulatory comparison. Results show that increasing the hydrogen content raises the flame temperature and NOx emissions while reducing CO and unburned hydrocarbons; a higher equivalence ratio elevates temperature and NOx with Φ = 0.8 balancing efficiency and emission control; and reducing load significantly lowers furnace temperature and NO emissions. Notably the boiler’s unique staged-combustion configuration (81% fuel supply to the central rich-combustion nozzle 19% to the concentric lean-combustion nozzle) was found to mitigate NOx formation by 15–20% compared to single-inlet burner designs and its integrated cyclone blades (generating maximum swirling velocity of 14.2 m/s at full load) enhanced fuel–air mixing which became particularly critical for maintaining combustion stability at low loads (≤20%) and high hydrogen blending ratios (≥20%). This study provides quantitative trade-off insights between combustion efficiency and pollutant formation offering actionable guidance for the safe efficient operation of hydrogen-enriched natural gas in industrial boilers.