Browse Topic: Energy conservation

Items (4,567)
For the single-screw extrusion process of solid propellant, the geometric optimization of the homogenization section faces a core problem: the high coupling between pressure establishment, material transport and energy consumption, and it is difficult to achieve a balance between different performance indicators by traditional empirical methods. Therefore, a numerical optimization framework combining CFD simulation and genetic algorithm is constructed to systematically explore the optimal screw geometric configuration. Propellant slurries are regarded as non-Newtonian fluids and are described by the Arrhenius temperature-dependent Bird-Carreau model, on which the flow field, pressure field and temperature field are solved. The key geometric parameters such as outlet core diameter, pitch, front and rear wedge angle, and thread width are selected as the optimization variables, and the ratio of pump power to shaft power is used as the objective function of energy efficiency to measure the degree of mechanical energy conversion into effective pressure work, and thermal safety constraints are introduced to control the upper limit of propellant temperature. The optimization results show that compared with the initial configuration, the volume flow rate is increased by 123% and the energy efficiency is only slightly reduced under the premise of maintaining a stable pressure drop. The flow field analysis shows that the optimized structure enhances the resistance-led conveying capacity and effectively inhibits the backflow phenomenon. Further analysis shows that the design with a larger pitch and narrower thread can reduce energy consumption while increasing the output, but its pressure accumulation ability is significantly weakened, revealing the inherent trade-off between screw geometry and pressure generation, conveying efficiency and energy consumption. The resulting optimized configuration achieves a good balance between multiple properties, which provides a theoretical reference for the continuous extrusion process of high-performance solid propellants.
Tang, Zhuang, Jiang, Ye, Mei, Mei, Wu, Wei-Tao
To support aviation decarbonization and improve overall propulsion efficiency, this paper proposes a hybrid propulsion architecture integrating a proton exchange membrane fuel cell (PEMFC) with a turbofan engine. The proposed parallel hybrid configuration achieves efficient energy conversion through the thermodynamic coupling of key components, including the heat exchanger, ducted fan, compressor, and combustor. A thermodynamic model is developed for parameter matching and system analysis. Results indicate that, at the design point, the overall system efficiency reaches 0.36, with a thermal efficiency of 0.42 and a propulsive efficiency of 0.82. Compared with the baseline CFM56-3C1 engine, the proposed system shows improved fuel economy and environmental performance, achieving a specific fuel consumption of 5.8 g/(s·kN), NOx emissions of 0.0063 g/kg-fuel, and a noise level of 92 dB. Exergy analysis further indicates that the primary exergy destruction occurs within the fuel cell (20%) and during combustor heat transfer (18%). These findings suggest that multi-energy pathway coupling can reduce fuel consumption and emissions, providing a potential approach for low-carbon aviation propulsion systems.
Huang, Mengxuan, Ji, Zhixing, Huang, Jiao, Xu, Zibo, Yao, Yunan, Cao, Zhipeng, Wang, Zhanxue
Aerospace & Defense Technology: Oct 202626AERP1010/8/2026
Terabit Optical Communications in Space: Engineering High-Speed Networks for Data Centers in Orbit Mild Hybrids: A Current-Gen Bridge to Electrifying Military Ground Vehicles The Integrated and Flexible Approach to Large-Scale Metrology: How Integrating Laser Trackers and Modular Arms Creates a 'Unified Nervous System' The Defense Industry Continues to Meet CMMC Phase II Requirements Despite 60-Day Pause In Space, No One Can Hear You Stream AMD to Bring UCIe Connectivity to Select Versal Adaptive SoCs How Special Interface Gages Provide Microscopic Precision for Designing Ballistic Missiles The pristine precision needed to certify the nation's underwater nuclear deterrent is anchored on the talents of civilian scientists at a Navy laboratory in Southern California. Rapidly Testing Deployable Systems Sandia National Laboratories is evaluating portable security architectures that combine radar, drones, ground sensors, cameras and wireless communications networks into a single rapidly deployable system for remote and austere environments. Testing focuses on sensor integration, resilient communications and edge-based data processing to improve situational awareness while operating within real-world bandwidth constraints. Tailored Surface Vibrations to Improve Aerodynamic Performance in Passenger Jets University of Colorado Boulder researchers have demonstrated two new phononic flow-control concepts, super-resonance and scatterless interference, that use engineered subsurface vibrations to interact with boundary-layer airflow across a broader range of turbulence frequencies than previously possible. By delaying flow instabilities without altering a wing's external shape, the technology could reduce aerodynamic drag and improve fuel efficiency in passenger aircraft. New Type of Attack Can Slip Past the Defenses in Your Computer's Processor MIT researchers found a way to exploit a split-second gap in chip security - and used it to acquire a Linux system's password file. Army Tests Safer Electrical Connectors for Ground Vehicle Readiness U.S. Army DEVCOM Ground Vehicle Systems Center engineers are evaluating cadmium- and hexavalent chromium-free electrical connectors designed to reduce hazardous material exposure while maintaining corrosion protection, electrical performance, and long-term vehicle sustainment.
Total Cost of Ownership (TCO) is a key metric in commercial vehicle purchase decisions and evaluation of advanced technologies such as battery electric and fuel cell vehicles (BEVs and FCEVs). Inputs derived from aggregate operating data, such as annual miles of travel and average fuel efficiency, as used in most TCO tools, may be inadequate for assessing technologies in specific applications. To provide more accurate estimates, the Transportation Technology Total Cost of Ownership (T3CO) model integrates vehicle simulation using the Future Automotive Systems Technology Simulator (FASTSim™). T3CO incorporates opportunity costs that may arise when technologies do not provide equivalent performance to conventional powertrains, such as reduced payload capacity and added downtime for more frequent and longer duration refueling. While past analyses used single duty cycles representative of average daily distance and energy per mile, fueling dwell time is nonlinear with respect to daily energy requirements and may not be captured with representative cycles. In this study, T3CO is applied to real-world operational data collected over 32 months from conventional Class 5 work trucks in three fleets, covering a variety of use cases and variability in daily demands. Diesel, BEV, and FCEV powertrains were simulated over the full data set, for a total of 1,986 vehicle days and 145,919 miles each. Analysis of duty cycle variability results in up to a 61% difference in fleet-level weighted average TCO compared to analysis over a single representative day. While diesel and FCEV TCO results are sensitive to fuel cost, BEV TCO is sensitive to the downtime from occasional daytime charging present in the total life cycle and not reflected in a subset “representative day.” For the studied fleets, these findings alter conclusions about the relative cost-effectiveness of new technology options at both the vehicle and fleet levels.
Birky, Alicia, Panneer Selvam, Harish, Sigler, Cory, Carow, Kyle, Miller, Eric, Ortmann, Walt, Tascillo, Mark
Waste heat recovery has become a critical research area in the quest for improving automotive energy efficiency. Internal combustion engines lose a large amount of their energy as heat through exhaust gases. Thermoelectric generation technology presents a promising approach to capturing and converting this waste heat into useful electrical energy. In this work, a theoretical study on the application of thermoelectric generators (TEGs) for battery charging by converting waste heat from internal combustion engine exhaust into usable electrical energy is proposed. A prototype system incorporating TEG modules was designed focusing on the minimization of back pressure; flow of exhaust gas is ensured through a circular internal cross-section. Thermal simulations were performed using Ansys Workbench, and computational fluid dynamics (CFD) analysis was conducted to quantify the back pressure. Two heat exchanger materials, aluminum and copper alloys, were evaluated for their heat transfer performance. The results indicate that copper achieves superior heat transfer, with hot-side temperatures approximately 8.6% to 23.9% higher than aluminum. However, aluminum remains a viable alternative due to its lightweight and cost-effectiveness. With the cold side being maintained at 91°C to simulate realistic engine coolant conditions, the experiment shows that a series-parallel configuration of six TEG modules (three in series × two in parallel) can effectively generate the necessary voltage (13–15 V) and current (3.5–7 A) to charge a 12-V automotive battery. CFD analysis confirmed that the circular internal geometry produces low back pressure, with pressure drops of 28 Pa, 63 Pa, and 168 Pa for inlet velocities of 25 m/s, 40 m/s, and 70 m/s, respectively. This research underscores the potential of TEG-based battery charging systems in enhancing energy efficiency, though further development is required for real-world automotive integration. Future work could focus on on-vehicle testing, optimizing thermoelectric materials, and integrating advanced cooling mechanisms and maximum power point tracking controllers to improve overall system viability.
Satheesh, Amal, Satheesh, Akul, Pillai, Ashwin S., Mahisankar, J.S., Sreejith, B.J.
Traditional Linear Circuit Analysis (LCA) relies on steady-state voltage assumptions that are fundamentally incompatible with battery-exclusive propulsion architecture. Whilst LCA remains valid for hybrid systems, where an auxiliary source actively regulates the State-of-Charge (SOC), it fails when analyzing non-passive, constant-power loads. In pure electric architecture, the time-dependent decay of the discharge voltage forces a continuous, non-linear increase in current to satisfy mechanical power demands. A time-dependent power flow methodology is introduced to resolve this theoretical divergence. Using the conservation of energy operating explicitly within the power domain, the time-dependent coupling of current and voltage can be modeled. This approach supersedes steady-state approximations for higher fidelity predictions for component efficiency, system heat generation, and battery capacity requirements for pure electric propulsion systems. Citation: N. Ingarra, K. J. Kobus, J. G. Kobus “TIME-DEPENDENT POWER FLOW MODELING FOR NONPASSIVE LOADS IN BATTERY ELECTRIC PROPULSION ARCHITECTURES” In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA, Novi, MI, Aug. 11-13, 2026.
Ingarra, Nicholas A., Kobus, Krzysztof (Chris) J., Kobus, Jadon G.
This study compares the energy efficiency of a real battery pack and a simulated battery pack using a hardware-in-the-loop battery emulator, through experimental testing on a dedicated inertia dynamometer for light quadricycles. The investigated LiFePo4 battery pack has a nominal voltage of 48 V and a nominal capacity of 100 Ah. Initial characterization identified a reduced State of Health based on capacity (SOHC), with a measured usable capacity of 48 Ah (from the nominal 100 Ah) and a corresponding reduction in charge acceptance capability. The emulator was configured to replicate the degraded battery characteristics, including the open-circuit voltage (OCV)-SOC relationship, internal resistance, and current limitations, enabling a direct comparison between simulated and experimental dynamic behavior. The experimental setup was designed to overcome the limitations of conventional chassis dynamometers for low-mass, independent four-wheel-drive quadricycles operating without mechanical friction braking systems. Multiple driving cycles were reproduced using a PLC-based closed-loop control system, with data acquisition performed via CAN communication. The comparative analysis highlights significant differences during regenerative braking events. While the emulator accurately reproduces baseline electrical behavior under mild operating conditions, the aged battery exhibits strong limitations during both high-power acceleration and severe deceleration phases. In particular, increased internal resistance and transient electrochemical polarization lead to premature saturation of charge acceptance, resulting in rejection of high-frequency current transients. Consequently, the experimentally observed energy recovery is significantly lower than the theoretical values predicted by the emulator. In addition, due to the absence of mechanical braking, the reduced regenerative capability directly leads to speed tracking deviations, as the required braking torque cannot be fully achieved. These results identify battery degradation as a key physical constraint affecting both energy efficiency and dynamic braking performance, highlighting the importance of improved electro-thermal and aging-aware model calibration for realistic system-level simulations.
Sementa, Paolo, Vaglieco, Bianca Maria, Altieri, Nunzio
Achieving significant reductions in energy consumption and CO₂ emissions in the transportation sector is a key challenge for sustainable mobility, particularly for vocational trucks operating under demanding driving and duty cycles. Beyond technological advancements in powertrain design, energy efficiency can be improved through optimized driving strategies. In this context, eco-driving has emerged as an effective approach to reduce energy consumption by optimizing the speed profile under given operational constraints. Eco-driving optimization strategies are particularly well suited for predefined and repetitive driving cycles, such as those typically encountered in waste collection. This work presents a comparative analysis between electric and internal combustion engine powertrain configurations applied to refuse trucks and vehicles, highlighting the impact of intrinsic differences on optimal speed profiles, energy consumption, and travel time. Both configurations are required to follow identical routes characterized by speed limits, mandatory stops, and comfort-related constraints. To address the optimization problem, the conventional longitudinal dynamics equations are reformulated from a time speed domain to a spatial speed domain through spatial discretization. The spatial domain is subsequently discretized, enabling the formulation of an optimization problem solved using dynamic programming to determine the optimal speed profile along real-world routes. The optimization framework is based on the minimization of a cost function composed of two main terms, normalized energy consumption and travel time variation, and a shape factor introduced to balance the tradeoff between energy efficiency and travel time. The objective of the study is to compare the two powertrain configurations under identical routes and constraints, analyzing energy consumption and travel time, and to identify the optimal compromise between time and energy consumption for each case. The results provide insights into the effectiveness of eco-driving strategies and underline the influence of powertrain architecture on optimal driving behavior.
Giacobbo, Andrea, Beltrami, Daniele, Villani, Manfredi, Tribioli, Laura, Iora, Paolo, Uberti, Stefano
Electric vehicles (EVs) impose more demanding operating conditions on wheel bearing systems due to increased vehicle mass, higher drive torque, and the need to maximize energy efficiency and driving range. These factors elevate the loads transmitted through the bearing to knuckle joint and often require higher clamp loads to ensure joint integrity. However, higher clamp loads amplify distortion of the wheel bearing outer ring, increasing rotational drag and reducing bearing durability. Controlling outer ring distortion is therefore critical for EV wheel bearing design, as well as for high performance vehicles that experience severe lateral loads at the hub to knuckle interface. This paper investigates key design considerations for optimizing the wheel bearing outer ring and its mounting interface to minimize distortion under elevated clamp loads. A comprehensive CAE-based Design of Experiments (DOE) is used to evaluate the influence of multiple bolt-mounting patterns including rectangular, square, and trapezoidal configurations and the relative alignment of the bolt pattern between the outer ring and knuckle. The study also compares the performance of M12 and M14 fastener variants across loading conditions representative of EV and high-performance applications. The results identify geometric and interface design parameters that significantly reduce outer ring out of roundness, thereby lowering drag torque and improving long-term bearing life.
Mandhadi, Chaitanya Reddy, Lee, Seungpyo, Bovee, Benjamin, Callaghan, Kevin
This study conducted a comprehensive economic evaluation of two major HEV architectures: the series-parallel configuration and the range-extended configuration. An analysis of these two configurations was performed using integrated vehicle and control models, allowing for a direct comparison of energy efficiency and operational economy. Findings show that the range-extended configuration has clear advantages in structural complexity, simplicity of control strategy, and development cost, while its energy consumption performance is similar to that of the series-parallel configuration. The results challenge the long-standing notion that range-extended configuration is less efficient, offering a new perspective on the design and configuration choices for hybrid electric vehicles.
Li, Ping, Guo, Wencui, Nie, Guole, Niu, Yazhuo, Bai, Bateer
Gravity heat pipes achieve efficient energy transfer through the evaporation and condensation of their internal working fluid, which steadily conducts underground heat to the surface and thereby provides a continuous and stable heat source for road pavements in winter. Considering the snow and ice melting demand of road surfaces in winter, this paper establishes an indoor environmental simulation experimental platform to systematically investigate the influence laws of different working fluids on the start-up temperature, start-up pressure, heat transfer power, and other key performance indicators of L-shaped gravity heat pipes. Through experimental research and analysis, it is revealed that heat pipes with R-134a and R245fa working fluids can operate stably at a shallow geothermal temperature of about 25 °C, while the acetone working fluid heat pipe operates unstably under this condition. The heat pipe filled with R-134a working fluid achieves the maximum heat transfer power under shallow geothermal conditions, followed by the heat pipe filled with R245fa. Although the heat transfer power of the acetone-filled heat pipe is generally relatively low, its heat transfer power increases most significantly with the rise of the evaporation section temperature. Under low-temperature conditions, the thermal conductivity of the evaporation section increases with the rise in the heating temperature of the evaporation section, while that of the condensation section decreases with the increase in the heating temperature of the evaporation section. Through experimental research and comparative analysis, this paper deeply explores the application potential of gravity heat pipe technology in green highway construction, and evaluates the feasibility and economic benefits of its engineering implementation, which provides a scientific basis and engineering guidance for the selection of green energy in future infrastructure construction.
Wang, Zhen-kun, Yuan, Zhi-ming, Wang, Kang, Zhang, Wen-jun, Wu, Xiang-song, Liu, Guang-bo
The application of steam compressors in heating supply of coal-fired power units demonstrates significant energy-saving benefits, while also effectively addressing the operational constraints of steam supply at low loads, thereby achieving thermoelectric decoupling.. This study analyzes and compares the performance characteristics and operational ranges of three distinct mechanical steam compression technologies. Although centrifugal compressors exhibit a low single-stage pressure ratio, their operational flow rate and temperature ranges are better suited for coal-fired heating requirements. Three typical application scenarios of steam compressors in industrial steam supply for coal-fired power units are proposed: Steam compressors enable waste heat recovery by compressing turbine exhaust steam for heating purposes, increase pressure in branch networks of steam supply pipelines to achieve high-pressure steam delivery, and enhance industrial steam extraction pressure under low-load conditions to realize thermoelectric decoupling. This enables substantial improvement in both the energy efficiency and steam supply capacity of coal-fired power units. Based on practical application cases of steam compressor systems, the objectives of steam pressure and temperature elevation can be achieved. Through collaborative adjustment of the drive motor frequency and the recirculation valve, dual-objective control of outlet flow rate and temperature can be realized. An analytical model was developed to simulate compressor performance, and validation against actual operational data confirmed the model’s applicability for guiding operational practices and control simulations. The centrifugal steam compressor in actual operation demonstrates normal performance across all operational indicators under high-speed conditions, confirming its technical reliability in coal-fired heating applications and providing crucial references for the widespread adoption of steam compressor technology in steam supply systems of coal power units. It expands the steam supply parameter range of electro-thermal conversion systems, thereby making a positive contribution to renewable energy integration.
Zhang, Pan, Liu, Yan
Waste heat recovery from internal combustion engines (ICEs) is one potential option to improve overall vehicle efficiency. Rankine cycles based on engine coolant and exhaust heat sources have demonstrated their effectiveness in enhancing brake thermal efficiency. Critical to their success is the design of the heat exchanger for the evaporator, with shell-and-tube heat exchangers (STHEs) a common hardware choice. However, little experimental data exists evaluating STHEs with the pulsating flow encountered in the exhaust of ICEs. In addition, correlations for periodically varying flow do not appear to be used in the modeling of STHEs. To alleviate this limitation, this study combined experiments using a pulsating exhaust heat source from an ICE under low loads at a single engine speed with a one+one-dimensional model to evaluate tube- and shell-side heat transfer correlations for a STHE without baffles. Four working fluids, water, ethylene glycol, propylene glycol, and a 50/50 ethylene glycol–water mixture, were examined. The combined thermodynamic properties of an ethylene glycol–water mixture were the most effective based on an evaluation of heat exchanger effectiveness, overall heat transfer coefficient, exergetic efficiency, and entropy generation. A Pearson correlation analysis identified the inlet working fluid temperature as the parameter most strongly correlated with STHE performance due to its higher enthalpy. From a modeling perspective, the pulsating flow correlation of Al-Haddad and Al-Binally predicted greater heat transfer rates in the STHE. In combination with all shell-side correlations tested, simulations still underpredict performance relative to experimental results. An optimized correlation developed specifically for the geometry of this unbaffled STHE matched the experimental data more closely but likely overpredicted shell-side heat transfer. Monte Carlo uncertainty propagation based on sensor uncertainties showed that the differences in effectiveness and overall heat transfer coefficient exceeded measurement uncertainty. Furthermore, sensitivity analysis demonstrated the importance of accurate thermophysical property values and indicated that the underprediction likely reflects coupled limitations in both tube- and shell-side formulations, with correlations on each side exerting a comparable influence on predicted heat transfer.
Spickler, Bailey, Segares Dominguez, Maria Luisa, McGowan, Raymond, Depcik, Christopher
The transition toward low global warming potential (GWP) refrigerants, driven by increasingly stringent environmental regulations and carbon reduction targets, has imposed new requirements on thermal management systems (TMSs) for electric vehicles (EVs). These systems must ensure efficient operation across a wide range of ambient conditions while maintaining high energy efficiency and environmental compatibility. Among potential alternatives, R290 (propane) has emerged as a promising natural refrigerant due to its favorable thermophysical properties and low environmental impact. In this study, an R290-based dual secondary loop TMS is proposed and evaluated for wide-temperature-range EV applications. A one-dimensional system model was developed using Dymola and validated through experimental testing on a dedicated performance test bench. TMS performance was investigated under multiple steady-state operating conditions, including high-load cooling, battery fast charging, and low-temperature heating, and benchmarked against a conventional R1234yf-based direct TMS. The results demonstrate that the R290-based dual secondary loop system achieves improved performance compared to a conventional R1234yf direct system, with a coefficient of performance (COP) increase of 4.29% under high-load cooling conditions at 43°C and up to 27.27% under high-load heating conditions at −10°C. Furthermore, under extreme low-temperature conditions (−18°C), the system delivers a heating capacity of 7 kW with a COP of 1.8, demonstrating strong low-temperature adaptability without the need for auxiliary heating. The results confirm that the proposed R290-based dual secondary loop system provides significant advantages in energy efficiency and wide-temperature adaptability, offering a promising solution for next-generation EVTMSs.
Zhang, Yunpeng, Mohammed, Mustafa Mudassir, Gu, Yiliang, Zhou, Guoliang
With the rapid development of the global economy, issues such as the energy crisis and environmental pollution have become increasingly severe. Owing to their environmental friendliness, structural simplicity, and high energy efficiency, electric vehicles have attracted widespread attention. Electric drive technology serves as the most promising and versatile propulsion solution for battery electric vehicles, hybrid electric vehicles, and fuel cell vehicles. As an advanced mechatronic transmission system, the electric drive axle offers high transmission efficiency, flexible packaging, and ease of digital and active chassis control integration, and has thus been increasingly adopted in modern vehicle architectures. The differential is a key component within the electric drive axle, responsible for regulating the rotational speed difference between the left and right wheels and ensuring balanced torque distribution. It plays a decisive role in vehicle stability and traction performance. This study focuses on the reliability testing methodology for differentials in electric drive axles, primarily including the extraction of reliability test conditions and the feasibility analysis of the proposed testing scheme. Specifically, based on the parameters of a given electric vehicle, a Simulink model of the motor and differential is established, and a complete four-wheel-drive vehicle model is constructed. Through simulation under typical driving conditions, operational data of the rear-drive axle differential are obtained. The collected data are then preprocessed and subjected to dimensionality reduction using Principal Component Analysis. The selected principal components are further analyzed using K-means clustering to construct representative differential reliability test conditions. The limitations of existing testing methods are analyzed based on the simulated results and relevant literature. Finally, a reinforced fatigue testing method for the differential is designed according to the extracted test conditions, and the feasibility of the corresponding test bench is evaluated.
Zheng, Hongyu, Li, Ziyu, Wang, Dajiang, Tian, Kai
The rapid evolution of electric vehicles (EVs) has led to the development of innovative approaches to optimize ride comfort, handling, and the overall suspension performance. EVs introduce unique challenges due to their distinct weight distribution, powertrain dynamics, and noise characteristics, unlike their conventional internal combustion engine (ICE) counterparts. This paper outlines an advanced damping force modeling methodology using machine learning (ML) techniques to enhance the suspension design process for next-generation EVs. The analysis is based on data-driven ML algorithms, i.e., Gradient Boosting, Random Forest, and Neural Networks, to simulate the nonlinear and frequency-dependent phenomenon of dampers in different operating conditions. A comprehensive dataset, generated through simulation and experimental testing, captures the effects of road profiles, vehicle dynamics, and damping settings. Additionally, this research evaluates the impact of machine-learned damping force predictions on critical ride and handling metrics, including ride comfort, road-holding ability, and energy efficiency. The results demonstrate that the ML models can enhance the iterative design process considerably and help to create the adaptive suspension systems that will address the particular requirements of EVs. This paper contributes to advancing the state-of-the-art of the suspension modeling, incorporating the ML-based insights in the development cycle. It highlights the possibility of artificial intelligence to transform suspension design, paving the way for superior ride quality and vehicle performance in electric mobility.
Hazra, Sandip, Tangadpalliwar, Sonali, Khan, Arkadip
Improving the efficiency of electric vehicle (EV) transmissions can help to extend the driving range of EVs, and the EV oil used in these transmissions plays an important role. In this study, in order to enhance energy efficiency, we examined the effects of lowering viscosity, traction, and friction in EV oil. While friction modifiers (FMs) have been widely used as friction reduction technologies in the field of tribology for many years, we previously developed a new FM that reduces friction in drive units. We found that a combination of lowering viscosity and using the developed FM was effective for better energy efficiency. The oil formulated with the developed FM improved efficiency by approximately +0.8% to +0.9% compared to commercial EV oil. EV oil also requires cooling performance. We assumed that reducing heat generation through friction reduction would improve cooling performance and examined the effect of lowering viscosity, traction, and friction. Consequently, it was found that a combination of lowering traction and applying the developed FM is effective for reduction in parasitic heat losses. We also examined durability, which is an issue when reducing viscosity. The results suggested that the oil formulated with the developed FM had good durability for gears and bearings. Thus, we succeeded in developing an ultra-low-viscosity EV oil that has excellent energy efficiency and high cooling performance.
Nakamura, Toshitaka, Furuse, Takashi, Hasegawa, Shinji, Akahori, Shinya, Itou, Kimikazu, Sakurada, Soichiro, Akiguchi, Junnosuke
To address the ambiguity in the relationship between design parameters and energy characteristics in pneumatic systems caused by gas compressibility and low viscosity, which leads to design redundancy, this paper proposes a dynamic characteristic characterisation method based on the pneumatic frequency ratio. This aims to establish a correlation mechanism between system energy consumption and dynamic performance. By constructing a nonlinear dynamic model of a double-acting cylinder, the dimensionless aerodynamic frequency ratio (Ω) is defined to characterise the matching relationship between the system’s natural and operating frequencies. Analytical relationships between Ω and key design parameters—such as cylinder diameter and valve sound velocity conductance—are derived, thereby establishing a normalised similarity criterion. Through combined simulation analysis and experimental validation, the regulatory patterns of Ω on the dynamic characteristics of displacement, velocity, and pressure are systematically investigated. Results indicate that under consistent Ω conditions, the normalised dynamic characteristic error across aerodynamic systems with varying parameters can be controlled within 4%. A significant linear correlation exists between the frequency ratio and the amplitude of cylinder chamber pressure differentials, with errors below 3%. The study further reveals that Ω exerts a nonlinear regulatory effect on system responsiveness and stability: increasing Ω enhances dynamic response speed but exacerbates pressure fluctuations, whereas decreasing Ω slows response but improves pressure stability. This methodology provides a theoretical foundation for energy-efficient design, parameter matching, and intelligent control of pneumatic systems, effectively addressing a gap in existing research on energy-dynamics coupling analysis.
Li, Mengru, Du, Hongwang, Wang, Jiajia, Yuan, Tingting, Xiong, Wei
In conventional braking systems, the kinetic energy of a vehicle is predominantly converted into heat through friction, a thermodynamically inefficient process. This not only causes progressive wear of components but also leads to the release of various materials, including heavy metals and organic compounds. With increasing concern over non-exhaust emissions, the search for innovative solutions becomes imperative. In electrified vehicles (xEVs), regenerative braking emerges as a strategic technology, converting kinetic energy into electrical energy to recharge the battery and extend range. This process not only enhances the vehicle's energy efficiency but also results in reduced frequency and intensity of mechanical brake usage. Consequently, there is a direct reduction in the wear of friction braking components, which translates into a significant mitigation of particulate matter emissions associated with this wear. The optimization of these systems occurs through Cooperative Regenerative Braking (CRB), which intelligently integrates with hydraulic braking. The primary challenge lies in managing the transition between modes to recover maximum energy without compromising safety and driver comfort. This technical paper explores how CRB employs 'torque blending' via advanced ECUs and software to adjust in real-time the proportion of each braking type, aiming for maximum energy recovery in diverse driving scenarios. To verify the effectiveness of this system, practical tests were conducted on a vehicle. The results obtained from these tests were conclusive, demonstrating significant gains in energy efficiency, with an increased battery recharging capacity during decelerations, optimized by the braking system. This improvement in efficiency directly impacts the reduction in the use of the conventional friction brake system and, consequently, a sharp decrease in particulate matter emissions. In this context, the intelligent and cooperative management of regenerative braking is a strategic and fundamental component for building a more sustainable future in vehicular mobility.
Batagini, Emerson, Romão, Bruno
Dual-motor architectures provide additional operating degrees of freedom for electric commercial vehicles (ECVs), but the integration of automated manual transmissions (AMTs) introduces torque discontinuities during gear-related mode transitions. Existing energy management strategies usually focus on steady-state efficiency optimization, while the mechanical feasibility of mode transitions is often considered separately or neglected. To address this issue, this study proposes a topology-aware hierarchical control framework for dual-motor ECVs. The framework combines an offline global efficiency map with an online transition-feasibility arbitration mechanism. In the offline layer, the energy-oriented operating mode and torque split are extracted over the vehicle-speed and wheel-torque domain. In the online layer, a topology-based transition matrix is used to identify mechanically singular mode transitions, and potentially torque-interrupting commands are re-routed through feasible bridge modes. The proposed method embeds powertrain topology constraints into the real-time implementation of an offline optimal map, thereby complementing conventional global optimization methods with transition-feasibility arbitration. Simulation results under the CHTC driving cycle show that the proposed strategy improves torque continuity during mode transitions while retaining most of the energy-saving benefit of the unconstrained efficiency-oriented strategy. Compared with the rule-based strategy, the proposed method reduces SOC-equivalent energy consumption by 10.7%, and recovers 65.5% of the DP-achievable energy-saving potential. Hardware-in-the-Loop (HIL) results further demonstrate that the proposed online arbitration logic can be executed within the controller sampling period.
Song, Dafeng, Chen, Lexin, Zeng, Xiaohua, Ni, Lixin
In an ever-evolving landscape of emission regulations, charging infrastructure, customer demands, fuel/energy costs and decarbonization goals, heavy-duty on-road vehicle manufacturers continue to evaluate alternative powertrain technologies. While most heavy-duty vehicle manufacturers now have battery electric vehicles (BEVs) in their portfolio, significant challenges of charging infrastructure, range anxiety, payload capacity reduction and upfront costs have contributed to their lower adoption rates. Plug-in hybrid electric vehicles (PHEVs) have significant potential of leveraging upcoming BEV infrastructure and component supply chains to reduce operating costs while still maintaining longer range and payload capacity benefits of conventional ICE powertrains. This article applies a model-based approach to evaluate multiple Class 7–8 heavy-duty powertrain configurations. A system-level (1D) model of the conventional diesel ICE-based truck was developed in GT-Suite and validated against on-road test data. Using the diesel ICE model as a baseline, system-level models for different hybrid configurations were adapted, and their powertrain architecture was optimized at the system level. Additionally, an equivalent consumption minimization strategy (ECMS) for energy management was also optimized for each of the hybrid powertrain configurations to maximize fuel efficiency and emission benefits. All the hybrid configurations were then compared against the conventional diesel ICE Class 8 truck in terms of performance (acceleration, top speed, gradeability and startability), fuel economy (real-world cycles and certification cycles), emissions, and range for long-haul applications. Unique to this approach is the simultaneous co-optimization of powertrain component sizing and supervisory control logic by utilizing a Genetic Algorithm–based optimization approach. Results indicate that all parallel hybrid architectures (P2, P2–P3, and P4) achieve performance (acceleration, top speed, gradeability, and startability) parity or improvement compared to baseline diesel architecture. P2-based architectures demonstrated a 12–14% improvement in fuel economy on representative real-world cycles when operating in a blended charge-depleting–charge-sustaining mode of operation, and a 4–6% improvement in fuel economy when operating in charge-sustaining mode alone. By quantifying these results across diverse topologies, this work addresses a significant research gap in the holistic evaluation of Class 8 hybrids, specifically, the trade-off between multi-speed electric drives, system-level mass increases, and real-world fuel economy, that remains underexplored in current literature.
Baburaj, Adithya, Paul, Sumit, Dhanraj, Fnu, Joshi, Satyum, Franke, Michael
This study prepares high-performance PI/VIP composite thermal insulation materials for buildings by integrating polyimide (PI) composite membranes and vacuum insulation panels (VIPs), and uses EnergyPlus to explore their impacts on building energy conservation, operating costs, and carbon emissions under different climates. Experimental results show the materials have low thermal conductivity, long service life, and excellent thermal insulation and flame-retardant properties due to their internal vacuum structure inhibiting heat transfer. Simulations in Jinan (tropical monsoon), Heilongjiang (cold temperate), and Shenzhen (subtropical humid) climates indicate that compared with traditional XPS and rock wool boards, buildings using PI/VIP composites achieve 21.3%, 34.7%, and 18.9% higher annual energy-saving efficiency respectively, with 27%-41% lower carbon emissions; the most significant effects in Heilongjiang highlight the material’s great promotion potential in severe cold areas.
Bian, Chenqian, Chen, Zhaofeng
In order to meet the needs of national energy conservation and environmental protection policies, a typical chassis structure lightweight method based on sensitivity analysis of 13 strength conditions was proposed. Firstly, the finite element model of the subframe of a certain model is established, and the impact strength and static strength of the subframe structure are analyzed by the finite element method. Secondly, the sensitivity analysis of 13 strength conditions was carried out for the 12 main sheet thicknesses in the finite element model. Based on the results of the sensitivity analysis, the plate thickness of the components that is conducive to lightweight and has little impact on the 13 strength conditions of the subframe was selected as the design variable. The size optimization was carried out with the goal of minimizing the mass of the subframe and the constraint that the maximum Von Mises stress of the unit, where each material is located, did not exceed the yield strength of the material. The optimization results show that the performance of the subframe under 13 strength conditions meets the requirements of the index, and the weight of the subframe is reduced by 1.37 kg / 9.6%.
Jing, Min, Jia, Zhilong, Zhang, Hualei, Liu, Minjie, Gan, Xinhua, Gao, Jinyu
Relying on the reconstruction project, the low-temperature modified asphalt pavement significantly reduces the construction temperature of the asphalt mixture by 40 °C compared with the traditional asphalt pavement, and improves the road performance of the material. By comparing the two mixture rolling schemes, the compaction effect of scheme 2 is better. For AC-13 mixture, the flexural tensile strength of USP-SBS composite modified asphalt mixture is 0.67 MPa higher than that of SBS modified asphalt mixture, and compared with SBS modified asphalt mixture, the final rut depth of USP-SBS composite modified asphalt mixture is 2.68 mm shallower than that of SBS modified asphalt mixture, and the total deformation rate is 43.8% lower than that of the latter. The post-construction quality evaluation shows that the stability of the low-temperature modified asphalt pavement test section under the bearing capacity and high-temperature-water coupling is better than that of the conventional road section, and the low-temperature stability is comparable to that of the two. This innovative application not only achieves energy saving and emission reduction but also provides a new solution for road construction under heavy traffic conditions.
Liu, Chuanfeng, Xu, Ke, Shi, Zheng, Hao, Jidong, Zhao, Liandi, Xianwei, Wang
Series hybrid electric vehicles (HEVs) employ an electric motor for propulsion, while the internal combustion engine operates solely as a generator under energy-efficient speed and load conditions. Owing to this architecture, series HEVs can achieve high fuel efficiency with a relatively simple control structure. However, conventional energy management systems (EMSs) often prioritize battery state-of-charge (SOC) stabilization, which can lead to frequent engine start–stop operations and unnecessary fuel consumption, particularly in short-trip driving. This study aims to enhance energy management performance in series HEVs by optimizing engine power generation timing based on predicted short-trip duration. A computationally efficient, rule-based prediction model is developed using real-world driving data, in which short-trip duration is estimated from vehicle speed and acceleration. Due to its low computational load, the proposed model is suitable for implementation in an onboard electronic control unit (ECU). The proposed control strategy initiates engine power generation when the battery SOC is low and the predicted trip duration is long, and suppresses generation when the SOC is sufficiently high or the predicted trip is short. A detailed vehicle model incorporating an engine, generator, electric motor, inverter, and battery is developed in Modelica to evaluate the proposed strategy. Simulation results demonstrate that the proposed EMS significantly reduces the frequency of engine start–stop events, leading to fuel economy improvements of 3.6% under the WLTC (excluding the extra-high phase) and 13.4% in a real-world urban–rural driving cycle, compared with a commercialized baseline vehicle. These results confirm the effectiveness and practical applicability of the proposed EMS for passenger vehicle applications.
Mizushima, Norifumi, Sato, Akira, Kuboyama, Tatsuya, Moriyoshi, Yasuo
To mitigate the risks of runway incursions during aircraft transitions between closely spaced parallel runways, major hub airports globally have implemented End-Around Taxiway (EAT) as an effective safety solution. Operational data from leading international airports confirms that EAT installations have successfully enhanced surface safety while maintaining operational efficiency. However, the EAT involves a longer taxiing route, resulting in higher fuel consumption and pollutant emissions. This study takes the example of a set of closely spaced parallel runways at a domestic airport to analyze the ground taxiing process of arrival and departure flights, proposing a dynamic allocation strategy for EAT operations that can achieve energy conservation and emission reduction during the taxiing process. Through simulation, its effective operational performance is studied.
Wang, Zinan, Ye, Bojia
The vehicles often accompanied by a huge impact in the collision process, high-quality and high-strength car-seats can better protect the safety of passengers. However, in the call for vehicle energy saving and emission reduction, the lightweight design of car-seats is imminent. Therefore, it is necessary to achieve lightweight seat weight while ensuring vehicle safety. Based on the dynamic condition of vehicle collision, this paper takes the rear seat of a certain model as the research object, takes multiple responses of the seat skeleton system as the target, establishes a multi-objective optimization model of the seat skeleton, determines the optimization result with the greatest comprehensive satisfaction, verifies the optimization result of the seat skeleton. The correctness and feasibility of the design method are proved.
Shao, Youlin, Ni, Weiyu, Chen, Daojiong, Cheng, Zhiqing
In order to improve the transportation efficiency of high-speed trains, reduce the operational energy consumption and ensure the on-time arrival of trains, the operation curve optimization is regarded as a key way to achieve the above objectives. In this paper, a distributed control method and system for grouped trains based on multi-objective running curve optimization is introduced. Firstly, the train dynamics equations are established by considering the combined forces during train operation and the train driving maneuvering strategy, combining with the line conditions, and dividing the train operating conditions; secondly, combining with the virtual grouping technology, the train units are kept in a high safety and smooth tracking operation with small intervals between the train units; and then the constraints, such as setting up safety protection distance and Then, the constraints of safety protection distance and space-time safety protection are set, and with energy-saving and comfort as the optimization goals, the multi-objective hiking optimization algorithm (MOHOA) is adopted to optimize the operation curve according to the train's working conditions; finally, the high-speed train tracking and operation system model is considered to have nonlinear and parameter-variable characteristics, and is susceptible to external factors. Finally, considering that the high-speed train tracking system model has nonlinear and time-varying characteristics and is easily affected by external disturbances, a distributed control law is designed for the optimized running curve, and a sliding mode control method is adopted for tracking operation. By optimizing the running curve of the train and realizing the precise protection strategy, the control method established based on the optimized curve can ensure the smooth running of the train while improving the efficiency of railroad transportation.
Jiang, Qiqi, Chen, Guangwu, Shi, Jianqiang, Wang, Dong, Si, Yongbo, Li, Peng, Zhang, Wentao, Yang, Yang
This study looks into the performance traits of a pure electric car that has a continuously variable transmission (CVT) system by doing careful simulations. The research is mostly about checking how well it performs dynamically and how much better its energy efficiency is compared to regular designs. With the help of AVL Cruise software, a detailed drivetrain model was made to test things like how fast it can accelerate, its top speed, how well it climbs hills, and how much energy it uses when driven in standard ways. The simulation results show some big improvements: the CVT car can go from 0 to 100 km/h in 12.92 seconds, which is 14% quicker than expected; it can reach a top speed of 179 km/h, 15% higher than planned; and it can climb really steep hills at a 41.33% gradient. The energy efficiency analysis also found that it uses less power, consuming just 15.88 kWh per 100km under NEDC conditions and 13.72 kWh per 100km in UDC cycles, which are 21% and 24% less than before. These results prove that the CVT works well in keeping the motor running efficiently by changing ratios all the time. The study points out the technical benefits of CVT systems in making performance and energy saving balanced, but it also finds some practical problems like environmental factors and system integration issues. This work gives useful ideas for making new electric vehicle transmission systems and hints at good ways to improve them in the future.
Chen, Haishan, Gong, Naifa, Pan, Yulong, Cai, Zhicheng, Gao, Yujie, Shen, Xiaobing, Fu, Xianlan, Chen, Keren
This paper presents the development of a speed controller for e-bikes, designed as part of an energy-adaptive assistance system. The controller provides riders with appropriate support along planned routes, based on the available battery capacity. The control concept is intended for integration into existing commercial e-bikes without requiring extensive modifications to the drive system. Therefore, the rider remains part of the control loop, adjusting the support mode according to instructions from the controller. The speed controller is implemented as a rule-based state machine, enabling comprehensible design and parameterization. Since the rider must manually switch between support modes while riding, the control logic incorporates hysteresis and dead times to ensure stability, prevent oscillations, and avoid frequent mode switching. The user interface is a smartphone application that issues visual and audio instructions for switching support modes. An initial, system-independent version that relied on GPS-based speed measurement was found to be insufficiently accurate for the control task. Furthermore, it was found that detection of the pedaling state was essential for proper operation. To address these issues, a Bluetooth-based hardware adapter was developed to access relevant signals from the e-bike’s CAN bus communication system. These include pedal power, cadence and speed, which are made accessible through reverse engineering of the CAN bus. The proposed concept is evaluated in a chassis dynamometer study with 13 participants on two test profiles: a synthetic gradient profile for assessing control stability and a realistic elevation profile for dynamic evaluation. Additional measurements taken with one of the test riders at different speeds demonstrate the system’s reliability and its potential to improve the energy efficiency. The results show that, with approximately the same power brought in by the rider, only 27% more electrical energy is required to increase the average speed by 45%.
Rauch, Yannick, Simmann, Gabriel, Schneider, Manuel, Goss, Christian, Kriesten, Reiner
The goal of reducing global CO2 emissions requires actions especially for the transportation sector. To achieve the goal, electric traction motors are frequently implemented in passenger vehicles, as well as in commercial vehicles like heavy-duty trucks or buses. Particularly electric city buses have the potential to reduce the local emissions in urban areas and provide local exhaust-emission-free mobility. While their number of registrations rises, research focusses on the improvement of the overall system in order to increase energy efficiency. High importance is gained by the thermal management of the whole system. This research investigates a simulative approach to improve the thermal management and therefore the energy efficiency of an electric city bus. The different thermal components of an electric city bus like drive system, battery system and heating, ventilation and air conditioning system (HVAC system) are modelled. Their thermal behavior has been validated in previous research. Based on the validated model, this study proposes an improved thermal management that, state-dependent, combines the thermal circuits of the single components to reduce the overall energy demand. Cooling or heating is provided by the HVAC system. Furthermore, the simulation utilizes real driving cycles of a city bus in the Hamburg area. Measurement data from an entire year are examined by a cluster analysis that results in typical application profiles for urban bus traffic. These profiles are used as basis for further research. An operating strategy for the thermal management of an electric city bus under real driving conditions is developed using the simulation model. Results are presented, which show that the overall energy demand decreases due to an improved, application profile-dependent thermal management system.
Schäfer, Henrik, Hellberg, Tobias, Meywerk, Martin
Hybrid-electric (xHEV) and fuel cell electric vehicles (FCEVs) are expected to play a crucial role in the transition towards sustainable mobility in both the individual and commercial transportation sectors. As their market share increases, there is a need for advanced research to enhance overall vehicle efficiency – particularly through optimized energy management systems. For FCEVs, an optimal energy management strategy is essential to ensure safe and durable operation. For xHEVs, thermal management serves as a central lever for improving efficiency and controlling emissions, making it an integral part of the overall powertrain development process. Considering today’s regulatory landscape, these aspects must be addressed early in development. Consequently, a holistic methodological framework is required, enabling not only technical robustness but also economic benefits, such as reducing engineering effort through effective frontloading. This methodology is composed of integrated simulation and testing approaches to develop components, systems, and operation strategies for future vehicles. Building on component- and system-level evaluations conducted at a dedicated thermal system testbed (ThermoLab), vehicle-level testing is required to calibrate and validate the laboratory results. To bridge the gap between the testbed and real driving events, an innovative approach is developed to replicate essential real-world boundary conditions, with particular focus on thermal and hydraulic conditions. The combination of a dedicated low-temperature extension chamber and an innovative dynamic coolant conditioning unit enables the energy-efficient transfer of thermal and hydraulic boundary conditions to a classic chassis dynamometer that was previously incapable of low-temperature testing. While the dedicated low temperature extension chamber transfers low temperature boundary conditions to the vehicles surrounding, the dynamic conditioning unit (Dynamic Module III) enables the accurate reproduction of relevant temperatures within the vehicle’s powertrain. This study demonstrates an innovative approach for the energy-efficient transfer of real-world low-temperature boundary conditions on a chassis dynamometer incorporating low-temperature extension and dynamic conditioning units as part of a holistic development methodology.
Lavall, Philipp, Beidl, Christian, Fiore, Luis, Papavasileiou, Ioannis, Hohenberg, Günter, Kalski, Christian
This paper assesses the efficiency limits of light-duty vehicle propulsion systems based on reciprocating internal combustion engines (ICE) in the current state of the art and in the next five-year horizon, considering their combination with technologies such as electric turbocharging and hybridization, while excluding plug-in hybrid configurations so that fuel remains the primary onboard energy source. A systematic methodology is applied to evaluate the influence of key variables—heat transfer, air–fuel ratio, and compression ratio—on engine performance, integrating these variations into a simulation model to capture their interactions and effects. The resulting parametric study enables the generation of new engine maps that exploit synergies between parameters and enhance the prediction of engine behaviour across different operating conditions, forming the basis for assessing potential advancements in hybrid powertrain architectures. These maps are then used to define performance expectations for hybrid vehicles, identifying optimal parameter combinations to guide future technology development and improve efficiency in hybrid powertrain design. The proposed powertrain architectures are integrated into a representative vehicle model, considering two vehicle typologies: a compact passenger car and a sport utility vehicle (SUV). To quantify the potential fuel-consumption benefits, an intelligent energy-management algorithm is implemented to supervise and optimize system operation over a WLTC driving cycle. The results indicate that the proposed configurations can achieve fuel-consumption reductions exceeding 20%, demonstrating the effectiveness of both the powertrain designs and the control strategies. Overall, the findings highlight the significant efficiency potential of advanced ICE-based propulsion systems when combined with near-term technologies such as electric boosting and hybridization, confirming the viability of these improvements and providing a robust basis for future hybrid vehicle development focused on maximizing energy efficiency in transportation.
Pla, Benjamin, Dolz, Vicente, Serrano, Jose R., Gómez-Vilanova, Alejandro, Oliva, Fermin, Cardenas, Maria, Ariztegui, Javier
The electrification of heavy-duty vehicles is a critical pathway toward improved energy efficiency in the freight sector. The current battery electric truck technology poses several challenges to commercial vehicle operations, such as limited driving range, sensitivity to climate conditions, and long recharging times. Estimating the energy consumption of heavy-duty electric trucks is crucial to assessing the feasibility of fleet electrification and its impact on the electric grid. This article focuses on developing a model-based simulation approach to predict and analyze the energy consumption of electric trucks by considering the impact of weather and geographical conditions on vehicle road load and auxiliary components power consumption, as well as the impact these factors have on driving range. Specifically, drayage trucks employed in logistics around maritime ports are used as a case study, with consideration of seasonal climate variations and geographical characteristics at different locations. The article includes results for three major container ports within the United States, providing region-specific insights into the energy requirements and driving range of the electric drayage trucks in these regions, which will inform decision-makers in integrating electric trucks into the existing drayage operations and plan investments for electric grid development.
Shiledar, Ankur, Villani, Manfredi, Lucero, Joseph N. E., Sun, Ruixiao, Sujan, Vivek A., Onori, Simona, Rizzoni, Giorgio
Large language models (LLMs) have shown remarkable capabilities for perceiving driving environments and making interpretable, logical decisions for autonomous driving. However, their potential for more comprehensive driving strategies, especially concerning energy efficiency, remains underexplored. Most existing studies primarily focus on driving safety, which may inadvertently increase energy consumption. To address this issue, this study explores the use of LLMs as high-level controllers to jointly optimize driving safety and energy efficiency. A textual prompt is designed for the LLM, incorporating few-shot examples that describe scenarios, states, and actions. The LLM processes the scenario and state prompts describing the surrounding traffic environment. It generates a high-level control signal, which is then translated into low-level vehicle motion commands in a high-fidelity traffic simulator with realistic physics, vehicle dynamics, road slopes, and network topology. Experiments in campus-scale digital twin car-following scenarios demonstrate that the proposed LLM-based framework achieves an average reduction of 4.16% in energy consumption compared to the reinforcement learning paradigm, while maintaining driving safety and providing interpretable high-level decision-making. This study highlights the potential of LLMs for longitudinal eco-driving applications under the evaluated simulation settings, extending previous LLM-based autonomous driving research that primarily focused on safety to also consider energy efficiency.
Wang, Haoyu, Li, Zhenning, Wang, Siying, Zhou, Zijing, Zhang, Xiang, Yang, Zhifeng, Ou, Shiqi (Shawn), Qi, Hao
Heavy-duty vehicles significantly contribute to greenhouse gas emissions and urban air pollution, especially during cold-starts and transients when engine and aftertreatment efficiencies drop. Waste heat recovery (WHR) via Organic Rankine Cycle (ORC) systems offers a practical solution to improve fuel efficiency and cut CO₂ in real-world heavy-duty operations. This study examines ORC-based WHR integration into conventional and hybrid powertrains of an Isuzu FTR850 truck, analyzing four configurations: Shell-and-Tube or Plate heat exchangers with simple or regenerative ORC layouts. For hybrids, it compares two engine sizes and energy management strategies: an optimized fuzzy logic approach versus constant-power operation to enhance exhaust heat recovery. A validated quasi-static simulation framework is used to predict fuel consumption and exhaust properties over representative duty cycles. 2D performance maps using exhaust temperature and mass flow as inputs are used to model the WHR under off-design conditions. Results show that the recovery of waste heat WHR depends on the hybridization level and strategy. Conventional powertrains benefit most from Shell-and-Tube exchangers, recovering ~2 kWh of electrical energy per 8-hour cycle and reducing fuel consumption by 0.5%. Hybrid setups recover up to 3.9 kWh from exhaust gases with a simple layout coupled with a Shell-and-Tube heat exchanger under constant-power control. Electricity is used to support onboard auxiliaries and battery charging, further lowering fuel demand (-44%) and emissions. Finally, a multi-objective optimization was performed to exploit the synergy between hybridization and WHR while maintaining acceptable payload and battery operating conditions.
Donateo, Teresa, Morrone, Pietropaolo
This work investigates the integration of a Sorption Thermal Energy Storage (TES) into the Heating, Ventilation and Air Conditioning (HVAC) system of electric vehicles. The proposed device reduces the energy demand for cabin heating under winter conditions, leading to a driving range increase. The TES dehumidifies the cabin air through a desiccant bed (zeolite 4A), preventing window fogging, enabling higher air recirculation rates, and consequently reducing the required heating power. An experimentally validated numerical model was used to analyze the adsorption and regeneration processes and to identify suitable operating conditions. Regeneration was found to be effective at moderate temperatures (from 120°C), with a counter-current airflow configuration providing faster and more efficient desorption compared to parallel-flow one. A simplified model integrating TES, HVAC unit and cabin was developed and used to compare different configurations. Heating energy consumption with and without TES under different ambient conditions, passenger loads, airflow rates, and regeneration states was evaluated. Heating energy savings ranged from 19% to 71%, increasing with higher external humidity. Considering the desiccant bed volume, equal to 1.65 L, electric energy savings up to 1.7 kWh L-1 for heat pump systems and 3.3 kWh L-1 for electric heaters were estimated, corresponding to a potential driving range increase of 13.4 km L-1 and 33.5 km L-1, respectively. Preliminary TES tests on a mock-up vehicle confirmed the effective dehumidification capacity of the proposed technology.
Verlingieri, Rebecca, Calabrese, Luigi, Freni, Angelo, Marocco, Luca, Scudeler, Gabriele, De Antonellis, Stefano
The reduction of Greenhouse Gas (GHG) emissions represents a key challenge for the transportation sector, requiring the adoption of renewable fuels capable of ensuring both environmental benefits and compatibility with existing internal combustion engine technologies. In this context, bioethanol emerges as a viable solution for Spark Ignition (SI) engines, offering a low life-cycle CO₂ footprint and favorable combustion characteristics. Nevertheless, despite its well-known advantages under steady-state operation, the widespread use of high-ethanol-content fuels is still limited by critical issues during engine cold start. The aim of this work is to experimentally investigate the influence of ethanol content on cold-start behavior and idle warm-up transient operation of a Naturally Aspirated (NA), Port Fuel Injected (PFI) SI engine. The experimental campaign was carried out under idle conditions using four fuels with increasing ethanol content, namely commercial gasoline (E5), E30, E60, and neat ethanol (E100). Cold-start and full warm-up tests were performed starting from ambient temperature, while additional dedicated experiments were conducted on E100 to evaluate startability under different initial engine wall temperatures. The results show that increasing ethanol content has a limited impact on the overall warm-up duration, while slightly reducing engine wall and exhaust gas temperatures. Conversely, E100 exhibits pronounced startability issues at low initial wall temperatures, requiring multiple cranking attempts to achieve stable idle operation. A minimum wall temperature threshold in the range of 25-30 °C was identified as necessary to ensure reliable cold start with E100. The outcomes of this study provide experimental evidence of the key role played by engine thermal conditions in enabling stable operation of ethanol fueled SI engines during cold start.
Falbo, Luigi, Falbo, Biagio, Perrone, Diego, Castiglione, Teresa
The ongoing efforts for reduction of the traffic-related greenhouse gas emissions and, at the same time, the mitigation of harmful pollutant emissions from vehicle exhaust emissions are important development tasks for the entire automotive industry worldwide according to demand to provide clean and efficient products. Further tightened fleet average FE standards and ultra-low limits for exhaust emissions require the continuous development of new propulsion system types. Due to the given reluctance of the end customer and corresponding low acceptance of fully electrified vehicles, especially in the commercial vehicle segment, new and innovative topologies are needed to meet regulatory requirements and maintain the high versatility of today’s dominating solutions. For further optimization of operating conditions with enhanced fuel efficiency, the technical strategy is also determined by uplifting the attractiveness of electric driving incl. the avoidance of areas with poor ICE efficiency and as well as the coverage of emission-critical operations by electric propulsion. In this context, the support provided by an electric drive on board the vehicle in a combined drive system is becoming increasingly important. This article discusses accordingly various platform strategies for hybridized Diesel powertrains in different sectors of commercial vehicle applications and delivers a comprehensive comparative analysis of different hybrid drive concepts. Specifically, several hybrid powertrain configurations that extend an electric drive platform (hybridized BEVs), such as series and parallel-series topologies, are compared with traditional parallel hybrid powertrain topologies based on internal combustion engines (ICE). The study focuses mainly on two different cornerstone applications: a large light commercial vehicle, ranging from 3,5 to 6,5 to. and a heavy-duty long-haul truck with 40…44 to. gross vehicle weight. It evaluates the advantages in terms of CO2 emissions and Diesel fuel savings and investigates the effects on emission controls aspects. In addition to technical comparisons, the paper addresses also regulatory demands and end customer merits, assessing the integrational effort and commonalities in components with pure ICE and battery electric topologies. Furthermore, it explores the additional impact of advanced operational strategies for Hybrid Diesel powertrains, incorporating insights from innovative observations from executed hybrid technology demonstrator vehicles.
Koerfer, Thomas
Improved energy efficiency and lower CO2 emissions are the two major drivers for the emergence of E-mobility. Growth of electric vehicles (EVs) has sustained ever since their introduction till 2020 and has substantially increased thereafter. EVs require specialized lubricants, which are different from conventional lubricants mainly due to the addition of new hardware technology including e-motor, inverter, battery, and new materials (copper windings, elastomers, plastic, and other materials). Lubricant when used in an advanced powertrain electric vehicle specifically in E-powertrains may encounter the e-motor and must deliver unique performance attributes such as optimal electrical properties, thermal management, and material compatibility apart from the traditional features including extreme pressure, friction performance, oxidation, and wear control. In the current study, we have investigated conventional GL5, manual transmission fluid (MTF), automatic transmission fluid (ATF), and dedicated e-fluids to understand additive and viscosity effects on aforesaid performance traits. Our study emphasized that additive chemistry plays a significant role on key properties such as electrical properties, corrosion resistance, oxidation resistance, and tribological performance.
Katta, Lakshmi, Seth, Sarita, Singh, Sandeep, Bhardwaj, Anil, Arora, Ajay Kumar
Decarbonization efforts achieved through electrification in nonroad mobile machinery can realize a reduction in fuel consumption of more than 20%, thanks to concepts familiar to light-duty passenger vehicles. This case study compares the results of a hybrid-electric material handler to its conventional counterpart, utilizing machine-specific drive cycles presented in part one of this paper series. The hybrid prototype features an extended-range electric vehicle (EREV) powertrain that demonstrated substantial energy efficiency improvements. Specifically, there was a reduction in equivalent fuel consumption of 75% when operating in electric-only mode, and 33% when maintaining the battery by charging with an on-board generator. Together, the efficiency improvements can be extrapolated over a low-intensity, 8-h shift characterized by significant idle time and highly dynamic engine load for a 47% reduction in net energy consumption. Key technologies that led to this improvement included engine downsizing and decoupling, regenerative braking, and an electrohydraulic pump unit with advanced controls. This study explains details of the powertrain architecture and subsystems that were implemented on a demonstration vehicle, control strategies used to meet project goals, and an analysis of energy consumption from testing on a closed course. Also included in this study is a discourse on comparison metrics that can be used for quantifying the energy consumption differences between hybrid-electric and conventional diesel powertrains in nonroad mobile machinery.
Czarnecki, Alexander, Goodenough, Bryant, Worm, Jeremy, Robinette, Darrell, LaTendresse, Phil, Westman, John, Subert, David, Heath, Matthew, Kiefer, Dylan, Black, Andrew
Volvo Trucks' revised VNR brings updated safety tech, improved fuel economy and driver comfort features to the regional haul segment. Volvo Trucks has continued its rollout of new models for every sector of the commercial truck market. The redesigned VNR is the latest model to see the spotlight. The new VNR naturally carries all of Volvo's latest safety tech, but also prioritizes maneuverability, fuel efficiency and configurability for a wide variety of fleet uses. “The VNR is an incredibly versatile truck,” said Maddie Sullivan, product marketing manager. “There are so many different configurations to meet our customer's needs. We offer four different cab sizes, three different axle configurations and two different chassis configurations.”
Wolfe, Matt
ZF foresees hybrid powertrain technology becoming more popular for commercial transport in the coming years, and it's working earnestly to be a major player in that realm. The supplier unveiled the TraXon 2 Hybrid transmission to the North American commercial vehicle market at last year's ACT Expo and is now evaluating the technology in real-world conditions. The next-gen automated manual transmission (AMT) is optimized to improve fuel efficiency for plug-in and full hybrid heavy-duty trucks and coaches, as well as special applications such as medium- to heavy-duty mobile cranes.
Gehm, Ryan
Sustainability needs to be practical. That was a point Peter Voorhoeve, president of Volvo Trucks North America, made clear at CONEXPO 2026 in Las Vegas. “We're running a business, so we are focusing a lot on efficiency and uptime,” he said, referencing the up-to-10% improvement in fuel efficiency with the new VNL. “That helps our customers to run their operations at a better pace and a lower cost, but at the same time we have a very positive impact on the climate.” Voorhoeve also teased the launch of a new vocational truck. “We are strong in long haul. We are a leading sleeper manufacturer, very strong in regional haul, and we now have renewed focus on vocational,” he said. “In August we will launch a new truck specifically for the vocational segment that's built on the same platform as the VNL and VNR.” (See page 22 for our feature story on the new VNR.)
Gehm, Ryan
Passenger comfort within vehicles and aerospace cabins relies on finely tuned management of temperature, air quality, and energy use. This paper proposes an integrated HVAC framework that combines zonal climate control, intelligent airflow distribution, and real-time sensor data to maintain thermal balance across different cabin zones. Leveraging predictive thermal load modelling and machine learning, the system anticipates environmental changes—such as sudden shifts in external temperature or passenger load—and proactively adjusts heating and cooling outputs. Simultaneously, air quality is enhanced through a multistage filtration system, active air purification technologies, and dynamic CO₂ concentration monitoring. Comfort assessment integrates PMV (Predicted Mean Vote) and PPD (Predicted Percentage Dissatisfied) indices to adapting environmental conditions. Simulations and early-stage prototypes improve energy savings and improve occupant comfort and air quality. The proposed HVAC approach is a promising avenue for enhancing passenger experience and operational efficiency in both ground and air mobility platforms.
Mudavath, Lehitha Sai, Patil, Ashish, Saha, Sudipta
This paper investigates the energy consumption characteristics of series hybrid aircraft with a focus on comparing conventional energy management approaches against an AI-powered optimization framework. The study comprehensively models the energy demands of a series hybrid aircraft across all major flight phases, including Idle & Ground Operations, Taxi, Takeoff, Climb, Cruise, Descent, Approach, Landing, and Rollout & Taxi. For each phase, detailed mathematical formulations are developed to capture power requirements and energy flow, incorporating real-time operational parameters to enhance the accuracy of the energy consumption estimations measured in kilowatt-hours (kWh). The AI-based optimization leverages advanced control strategies, specifically Model Predictive Control (MPC) and Reinforcement Learning (RL) algorithms, to dynamically manage the aircraft’s energy systems. MPC is employed to predict and optimize future energy usage by solving constrained optimization problems over a moving time horizon, ensuring efficient energy distribution while satisfying operational constraints. Concurrently, RL algorithms enable adaptive learning from operational data to improve decision-making in energy management, optimizing performance under varying flight conditions and uncertainties. Comparative analysis demonstrates that the AI-driven series hybrid aircraft achieves significant energy savings compared to conventional methods, quantified in both absolute kWh reductions and percentage improvements. These savings are particularly pronounced during overall phases such as Takeoff, Climb, and Cruise, etc. where optimal control of energy flows directly translates to improved efficiency and extended operational endurance. The findings underscore the potential of AI-integrated control systems in advancing sustainable aviation technologies by enabling smarter, energy-efficient hybrid propulsion. This paper provides a foundation for future development of intelligent energy management systems that can be deployed in next-generation hybrid series aircraft, contributing to reduced environmental impact and enhanced operational performance.
Kanchagar, Amogha
In a world first, researchers have used 2D materials, which are only an atom thick and retain their properties at that scale, unlike silicon, to develop a computer capable of simple operations. The development, published June 11 in Nature, represents a major leap toward the realization of thinner, faster and more energy-efficient electronics, the researchers said. They created a complementary metal-oxide semiconductor (CMOS), which is at the heart of nearly every modern electronic device, without relying on silicon. Instead, they used two different 2D materials to develop both types of transistors needed to control the electric current flow in CMOS computers: molybdenum disulfide for n-type transistors and tungsten diselenide for p-type transistors.
This paper presents a multi-physics modeling approach for a hybrid propulsion system designed for High-Altitude Long-Endurance Unmanned Aerial Vehicles (HALE UAVs), integrating solid oxide fuel cells (SOFCs), lithium-ion batteries, and a jet engine. A dynamic model was developed to analyze the coupled characteristics of pressure, temperature, and power under steady-state conditions. Simulation results demonstrate that the internally integrated system achieves efficient fuel and waste heat recovery, delivering a net power output of 300–700 kW, sufficient to meet the operational demands of HALE UAVs. Key innovations include a heat exchanger maintaining SOFC stack inlet temperatures above 850 K for optimal performance and a compressor-fan subsystem enhancing gas compression efficiency. Experimental validation confirmed the accuracy of the SOFC model, with simulated electrical characteristics aligning closely with empirical data. The proposed hybrid system addresses limitations in specific power and transient response while improving energy density, offering a viable solution for long-endurance flight missions. This study provides a foundational platform for advancing hybrid propulsion technologies in aviation.
Zhang, Lin, Zhang, Di, Zhao, Lulu, Li, Xi
Indoor thermal comfort is closely related to people’s health and work efficiency. Control systems typically consume a large amount of energy to maintain a comfortable thermal environment. Currently, reinforcement learning is widely applied to optimize thermal comfort control systems. However, existing research mainly adopts universal thermal comfort evaluation models that aim to satisfy the majority of people, which makes it difficult to quickly and accurately reflect the specific thermal comfort needs of individuals. As a result, the hot environment is neither comfortable nor energy-efficient in practical use. Therefore, this paper proposes an energy-saving personalized thermal comfort control method based on decision trees and reinforcement learning. First, decision tree learning is used to obtain an individual thermal comfort evaluation model from a small amount of historical data. Then, this individual comfort model is combined with energy consumption to form a reward function, which is used in reinforcement learning to derive personalized thermal comfort control strategies. The experiments show that, compared to traditional methods, this approach can improve user thermal comfort by 43.8% and achieve an energy-saving effect of 30.7%.
Li, Xianying
Against the backdrop of growing global demands for energy sustainability and stricter emission regulations for diesel engines, this study investigates the performance implications of incorporating cyclohexanol—a renewable oxygenated fuel—into diesel fuel blends. Using a marine medium-speed diesel engine as the experimental platform, the research systematically evaluates engine performance and emission characteristics across a range of cyclohexanol-diesel blend ratios under low, medium, and high load conditions. Experimental findings reveal multifaceted effects of cyclohexanol blending on engine operation. Combustion of the blended fuels enhances the engine’s dynamic performance, particularly under medium and high loads, where the maximum in-cylinder burst pressure exhibits a noticeable increase. This improvement is attributed to cyclohexanol’s oxygen-carrying capacity, which promotes more vigorous and sustained combustion reactions. In terms of emissions, increasing the proportion of cyclohexanol in the fuel blend leads to significant reductions in soot and carbon monoxide (CO) emissions, reflecting the cleaner-burning properties of the oxygenated component. However, this is accompanied by an uptick in nitrogen oxide (NOx) emissions, likely due to the elevated combustion temperatures generated by the more efficient fuel oxidation process. From an economic perspective, cyclohexanol blending at consistent load levels induces a postponement in the crank angle at which peak heat release occurs during combustion. This temporal shift prolongs the effective combustion duration, enabling more complete fuel utilization within the cylinder. Consequently, fuel consumption rates decrease, and overall engine efficiency improves, highlighting the potential of cyclohexanol blends to enhance operational economy in marine propulsion systems. In summary, this study underscores the complex trade-offs associated with cyclohexanol-diesel blends: while they offer tangible benefits in power output, fuel efficiency, and reduced particulate emissions, managing the increase in NOx emissions remains a critical challenge. The results provide a foundational framework for advancing biofuel applications in marine engines, emphasizing the need for integrated emission control strategies to optimize the balance between performance and environmental sustainability.
Chen, Ke, Yang, Chenxi, Wang, Yibin, Fan, Jinyu, Liu, Yuchen, Ye, Zixiao, Huang, Jialiang
Items per page:
1 – 50 of 4567