Search Results (281)

Driven by carbon neutrality and peak carbon policies, hydrogen energy, due to its zero-emission and renewable properties, is increasingly being used in hydrogen fuel cell vehicles (H-FCVs). However, the high cost and limited durability of H-FCVs hinder large-scale deployment. Hydrogen internal combustion engine hybrid electric vehicles (H-HEVs) are emerging as a viable alternative. Research on the techno-economics of H-HEVs remains limited, particularly in systematic comparisons with H-FCVs. This paper provides a comprehensive comparison of H-FCVs and H-HEVs in terms of total cost of ownership (TCO) and hydrogen consumption while proposing a multi-objective powertrain parameter optimization model. First, a quantitative model evaluates TCO from vehicle purchase to disposal. Second, a global dynamic programming method optimizes hydrogen consumption by incorporating cumulative energy costs into the TCO model. Finally, a genetic algorithm co-optimizes key design parameters to minimize TCO. Results show that with a battery capacity of 20.5 Ah and an H-FC peak power of 55 kW, H-FCV can achieve optimal fuel economy and hydrogen consumption. However, even with advanced technology, their TCO remains higher than that of H-HEVs. H-FCVs can only become cost-competitive if the unit power price of the fuel cell system is less than 4.6 times that of the hydrogen engine system, assuming negligible fuel cell degradation. In the short term, H-HEVs should be prioritized. Their adoption can also support the long-term development of H-FCVs through a complementary relationship. Full article

This paper presents a simulation framework for evaluating power flow, energy efficiency, thermal behavior, and energy consumption in electric vehicles (EVs) under standardized driving conditions. A detailed Simulink model is developed, integrating a lithium-ion battery, inverter, permanent magnet synchronous motor (PMSM), gearbox, and a field-oriented control strategy with PI-based speed and current regulation. The framework is applied to four standard driving cycles—UDDS, HWFET, WLTP, and NEDC—to assess system performance under varied load conditions. The UDDS cycle imposes the highest thermal loads, with temperature rises of 76.5 °C (motor) and 52.0 °C (inverter). The HWFET cycle yields the highest energy efficiency, with PMSM efficiency reaching 92% and minimal SOC depletion (15%) due to its steady-speed profile. The WLTP cycle shows wide power fluctuations (−30–19.3 kW), and a motor temperature rise of 73.6 °C. The NEDC results indicate a thermal increase of 75.1 °C. Model results show good agreement with published benchmarks, with deviations generally below 5%, validating the framework’s accuracy. These findings underscore the importance of cycle-sensitive analysis in optimizing energy use and thermal management in EV powertrain design. Full article

The presence of toxic gas emissions from conventional vehicles is worrisome globally. Over the past few years, there has been a broad adoption of electric vehicles (EVs) to reduce energy usage and mitigate environmental emissions. The EVs are characterized by limited range, cost, and short range. This prompts the need for hybrid electric vehicles (HEVs). This study describes the conversion of a 2022 Volkswagen Crafter (VW) 35 TDI 340 delivery van from a conventional diesel powertrain into a hybrid electric vehicle (HEV) augmented with synchronous electrical machines (motor and generator) and a BMW i3 60 Ah battery pack. A downsized 1.5 L diesel engine and an electric motor–generator unit are integrated via a planetary power split device supported by a high-voltage lithium-ion battery. A MATLAB (R2024b) Simulink model of the hybrid system is developed, and its speed tracking PID controller is optimized using genetic algorithm (GA) and particle swarm optimization (PSO) methods. The simulation results show significant efficiency gains: for example, average fuel consumption falls from 9.952 to 7.014 L/100 km (a 29.5% saving) and CO₂ emissions drop from 260.8 to 186.0 g/km (a 74.8 g reduction), while the vehicle range on a 75 L tank grows by ~40.7% (from 785.7 to 1105.5 km). The optimized series–parallel powertrain design significantly improves urban driving economy and reduces emissions without compromising performance. Full article

Hybrid electric vertical take-off and landing (HEVTOL) flying vehicles serve as effective platforms for efficient transportation, forming a cornerstone of the emerging low-altitude economy. However, the current lack of co-optimization methods for powertrain component sizing and energy controller design often leads to suboptimal HEVTOL performance. To address this, this paper proposes a hierarchical manifold-enhanced Bayesian evolutionary optimization (HM-BEO) approach for HEVTOL systems. This framework employs lightweight manifold dimensionality reduction to compress the decision space, enabling Bayesian optimization (BO) on low-dimensional manifolds for a global coarse search. Subsequently, the approximate Pareto solutions generated by BO are utilized as initial populations for a non-dominated sorting genetic algorithm III (NSGA-III), which performs fine-grained refinement in the original high-dimensional design space. The co-optimization aims to minimize fuel consumption, battery state-of-health (SOH) degradation, and manufacturing costs while satisfying dynamic and energy management constraints. Evaluated using representative HEVTOL duty cycles, the HM-BEO demonstrates significant improvements in optimization efficiency and solution quality compared to conventional methods. Specifically, it achieves a 5.3% improvement in fuel economy, a 7.4% mitigation in battery SOH degradation, and a 1.7% reduction in system manufacturing cost compared to standard NSGA-III-based optimization. Full article

Torque and velocity fluctuations in internal combustion engines (ICEs), particularly during idle and low-speed operation, can reduce efficiency, increase vibration, and impose mechanical stress on coupled systems. This work presents the design, simulation, and experimental validation of a passive balancing cam mechanism developed to mitigate fluctuations in single-cylinder internal combustion engines (ICEs). The system consists of a cam and a spring-loaded follower that synchronizes with the engine cycle to store and release energy, generating a compensatory torque that stabilizes rotational speed. The mechanism was implemented on a single-cylinder Honda^® engine and evaluated through simulations and laboratory tests under idle conditions. Results demonstrate a reduction in torque ripple amplitude of approximately 54% and standard deviation of 50%, as well as a decrease in angular speed fluctuation amplitude of about 43% and standard deviation of 42%, resulting in significantly smoother engine behavior. These improvements also address longstanding limitations in traditional powertrains, which often rely on heavy flywheels or electronically controlled dampers to manage rotational irregularities. Such solutions increase system complexity, weight, and energy losses. In contrast, the proposed passive mechanism offers a simpler, more efficient alternative, requiring no external control or energy input. Its effectiveness in stabilizing engine output makes it especially suited for integration into hybrid electric systems, where consistent generator performance and low mechanical noise are critical for efficient battery charging and protection of sensitive electronic components. Full article

This paper presents a methodology for systematically scaling vehicle powertrain and other models and an approach for using model parameters and scaling variables to perform controller design. The parameter scaling method allows for high degrees of scaling while maintaining the target performance metrics, such as vehicle speed tracking, with minimal changes to the model code by the researcher. A comparison of proportional-integral, Youla parameterization, ${\mathrm{\text{H}}}_{\infty }$, and hybrid Youla-${\mathrm{H}}_{\infty }$ controllers is provided, along with the respective methods for maintaining controller performance metrics across degrees of model scaling factors. The application of the scaling and various control design methods to an existing model of a hydrogen fuel cell and a battery electric vehicle powertrain allows for the development of a representative scale model to be compared with experimental data generated by an actual scale vehicle. The comparison between scaled simulation and experimental data will eventually be used to inform the expected performance of the full-size electric vehicle based on full-size simulation results. Full article

Integrating the electric motor with a multi-speed transmission is an effective way to improve the efficiency and performance of battery electric vehicles (BEVs). This paper innovatively proposes a design method for matching a single-motor and dual-speed dual-clutch transmission (2-Speed Wet DCT) powertrain system and constructs a variable speed efficiency model (VSEM) and constant speed efficiency model (CSEM) for the inverter, motor, and transmission. Research shows that the design parameters of the motor and transmission significantly affect the optimal powertrain system. This study uses an enhanced NSGA-II multi-objective genetic algorithm to optimize the driving performance of energy efficiency and powertrain cost under two different acceleration times (10 s and 12 s), with the key parameters of the motor and transmission as optimization variables and dynamic indicators as constraints, and compares VSEM and CSEM. The optimization results indicate that VSEM have better energy-saving effects than CSEM, with the energy consumption reduced by 3.7% and 3.3% under the two driving performances, respectively. The Pareto frontier further confirms that, for multi-speed transmission systems in electric vehicles, matching a high-power, high-torque motor with a smaller transmission ratio powertrain can achieve higher energy efficiency and thus longer driving range. Additionally, this study quantifies the correlation between energy efficiency and powertrain cost using grey relational analysis (GRA), with a result of 0.77431. Full article

The complexity and shortening of development cycles in the automotive industry, particularly with the rise in hybrid electric vehicle sales, increases the need for efficient calibration and testing methods. Virtualization using hardware-in-the-loop testbenches has the potential to counteract these trends, specifically for the calibration of hybrid operating strategies. This paper presents a dynamic closed-loop validation of a hardware-in-the-loop testbench designed for the virtual calibration of hybrid operating strategies for a plug-in hybrid electric vehicle. Requirements regarding the hardware-in-the-loop testbench accuracy are defined based on the investigated use case. From this, a dedicated hardware-in-the-loop testbench setup is derived, including an electrical setup as well as a plant simulation model. The model is then operated in a closed loop with a series production hybrid control unit. The closed-loop validation results demonstrate that the chassis simulation reproduces driving resistance closely aligning with the reference data. The driver model follows target speed profiles within acceptable limits, achieving an R² = 0.9993, comparable to the R² reached by trained human drivers. The transmission model replicates the gear ratios, maintaining rotational speed deviations below 30 min⁻¹. Furthermore, the shift strategy is implemented in a virtual control unit, resulting in a gear selection comparable to reference measurements. The energy flow simulation in the complete powertrain achieves high accuracy. Deviations in the high-voltage battery state of charge remain below 50 Wh in a WLTC charge-sustaining drive cycle and are thus within the acceptable error margin. The net energy change criterion is satisfied with the hardware-in-the-loop testbench, achieving a net energy change of 0.202%, closely matching the reference measurement of 0.159%. Maximum deviations in cumulative high-voltage battery energy are proven to be below 10% in both the charging and discharging directions. Fuel consumption and CO₂ emissions are modeled with deviations below 3%, validating the simulation’s representation of vehicle efficiency. Real-time capability is achieved under all investigated operating conditions and test scenarios. The testbench achieves a real-time factor of at least 1.104, ensuring execution within the hard real-time criterion. In conclusion, the closed-loop validation confirms that the developed hardware-in-the-loop testbench satisfies all predefined requirements, accurately simulating the behavior of the reference vehicle. Full article

Road transport represents a major contributor to air pollution, energy consumption, and carbon dioxide emissions in Switzerland. In response, stringent emission regulations, penalties for non-compliance, and incentives for electric vehicles have been introduced. This study investigates how these policies, along with shifting consumer preferences and vehicle design advancements, have influenced the composition of the Swiss new passenger car fleet. Using machine learning techniques, we segment passenger vehicles to analyze trends over time. Our findings reveal a decline in micro and small vehicles, alongside an increase in lower- and upper-middle-class vehicles, sport utility vehicles, and alternative powertrains across all segments. Additionally, steady increases in vehicle width, length, and weight are observed in all classes since 1995. While technological advancements led to reductions in energy consumption and carbon dioxide emissions until 2016, an increase has since been observed, driven by higher engine power, greater vehicle weight, and changes in certification schemes. Full article

The motor drive system is pivotal for vehicles, particularly in new energy applications. However, conventional hybrid systems, which combine generator sets and single batteries in parallel configurations, fail to meet the operational demands of large pure electric mining dump trucks under fluctuating power requirements—such as high reserve power during acceleration and robust energy recovery during braking. Traditional single-motor configurations struggle to balance low-speed, high-torque operations and high-speed driving within cost-effective ranges, often necessitating oversized motors or multi-gear transmissions. To address these challenges, this paper proposes a dual-motor symmetric powertrain configuration with a seven-speed gearbox, tailored to the extreme operating conditions of mining environments. By integrating a high-speed, low-torque motor and a low-speed, high-torque motor through dynamic power coupling, the system optimizes energy utilization while ensuring sufficient driving force. The simulation results under extreme conditions (e.g., 33% gradient climbs and heavy-load downhill braking) demonstrate that the proposed configuration achieves a peak torque of 267 kNm (200% improvement over single-motor systems) and a system efficiency of 92.4% (vs. 41.7% for diesel counterparts). Additionally, energy recovery efficiency reaches 85%, reducing energy consumption to 4.75 kWh/km (83% lower than diesel trucks) and life cycle costs by 38% (USD 5.34/km). Field tests in open-pit mines validate the reliability of the design, with less than a 1.5% deviation in simulated versus actual performance. The modular architecture supports scalability for 60–400-ton mining trucks, offering a replicable solution for zero-emission mining operations in high-altitude regions, such as Tibet’s lithium mines, and advancing global efforts toward carbon neutrality. Full article

Noise, vibration and harshness analyses are of great interest for the latest developments of the gearboxes of electric vehicles. Gearboxes are now the main source of vibrations, since electric powertrains are much quieter than internal combustion engines. Traditionally, the simulation of the non-linear gear dynamics is studied by first performing a series of preliminary static analyses to compute the static transmission error (STE). The STE (i.e., in the form of varying mesh stiffness) is then accepted as the system’s excitation source to compute the dynamic transmission error (DTE). This paper presents a novel approach to analyze the non-linear dynamics of gears which does not require any preliminary static analyses. The method consists of a frequency–domain approach based on the Harmonic Balance Method (HBM) and the Alternating Frequency–Time (AFT) scheme, allowing for much faster simulations when compared to the widely used direct–time integration (DTI). The contact between the teeth is modeled as intermittent and penalty based with a varying gap. The time–varying gap between the teeth is initially approximated to a step function that guarantees the design contact ratio. The methodology introduced is tested on a lumped parameter model of a spur–gear pair already proposed and simulated in the literature. The results obtained with the novel approach are compared with the DTI simulation of the model as a reference. The excellent match between the different approaches validates the reliability of developed methodology. Full article

Appropriate energy management strategy can further improve the fuel economy of plug-in hybrid electric vehicles (PHEV). Rule-based control strategies are dominant in actual vehicles because of their fast calculation and easy implementation. However, incorrect parameter settings and suboptimal control strategies may lead to substantial performance variations, preventing optimal fuel efficiency and emissions reduction. In this paper, the dynamic programming algorithm is implemented to design the control strategy for a dual-motor PHEV. The MATLAB/Simulink environment is used to construct models of the key components and powertrain controller, and simulation platforms for both rule-based and optimization-based strategies are established. Through the calculation results of dynamic programming (DP) algorithm, the rule of working mode switching and torque distribution is analyzed to improve the performance of rule-based control strategy. WLTC driving cycle simulation results show that the improved rule control effectively improves the economy of PHEV, and its comprehensive consumption per 100 km decreases by 2.853%. Full article

Electric vertical take-off and landing vehicles introduce challenges in powertrain design with short but high peak loads and low-load phases over longer periods of time during wing-borne flight. In this paper, three powertrain topologies are analyzed for a tilt-rotor urban air mobility vehicle with an expected entry into service after 2030. The powertrains are studied on the level of preliminary sizing for the design mission of the vehicle. The three powertrain topologies studied and compared are battery-only, fuel cell-only and a hybrid of the two energy sources. Parameter studies on the gearbox transmission ratio, the design point of the fuel cell system as well as the degree of hybridization were carried out. The combination of fuel cell and battery was found to be most beneficial in terms of mass when the fuel cell is sized for slightly more than cruise power. In flight phases with higher power requirements, the batteries would provide the additional boost. Full article

This paper presents an effective simplified model to optimize the mission power management supply for hybrid-electric aircraft in the conceptual design phase. The main aim is to show that, by using simplified representations of the aircraft dynamics, it is possible to achieve reliable results and identify trends useful for early-stage design, avoiding the use of more expensive and advanced methods. This model has been integrated into a multidisciplinary design framework, where the mission analysis, based on a simplified point mass dynamic model, focuses on splitting the power supply between electric and thermal power throughout the flight. An optimization algorithm identifies the time profiles of the supplied power, thermal and electric, to minimize fuel consumption. The power supplied by the thermal engine, modeled as a time piecewise function, is a design variable; a parametric study on the number of intervals composing this function is performed. The framework is used to propose a generalized approach for hybrid-electric power management optimization during the conceptual design iterations. This study showed that, for regional hybrid-electric aircraft, dividing the airborne mission into climb, cruise and descent is sufficient to define the optimum power split supply profiles. This allows for the avoiding of finer mission discretization, or the adoption of more complex simulative models, providing a very efficient model. Full article

Electric motorcycles feature a smaller size and lower weight than electric cars, meaning they have greater manoeuvrability and energy efficiency, which translate to a dynamic riding experience and reduced environmental footprint. From a thermal management perspective, one major challenge is how to maximise the heat dissipation efficiency of the battery system within the limited space available onboard since the battery system represents one of the largest thermal loads onboard. This paper investigates electric motorcycle modelling to facilitate prototype development, emphasising a compact, integrated cooling system for high-voltage powertrain components, including the battery, inverter, and motor. Particularly, the proposed battery model is structured across the pack–module–cell hierarchy, which makes it capable of distinguishing the thermal state of each individual cell and the cell-to-cell performance variations resulting from temperature effects. The integrated cooling system and multi-scale battery modelling method proposed in this paper allow for a quick comparison of performances between different battery module thermal designs, which is specifically suited for early-stage investigation of different concepts. A series and a parallel battery module thermal design are proposed and compared, with a focus on evaluating their impacts on system-level and component-level thermal performances as well as cell-level performance variations, including but not limited to temperature, state of charge, voltage, and state of power. Specifically, the serial thermal design provides better overall cooling efficiency and lower battery pack temperatures, while the parallel design significantly reduces cell-to-cell variations. Full article