Electric Propulsion Research Articles

Elucidation of spacecraft surface wear phenomena in the plasma environment emitted by electric propulsion vehicles based on spacecraft charging analysis

Professor Takanobu Muranaka, Chukyu University, Japan, is part of a collaborative research effort to investigate and elucidate surface wear phenomena in electric propulsion spacecraft vehicles. He and his team are exploring how injected plasma emitted by these vehicles interacts with the spacecraft, leading to potential electrical and mechanical issues. For example, the ions and electrons in the plasma can collide with the spacecraft, causing wear and tear. This can compromise the spacecraftâ–™s durability and lifespan. In order to analyse these interactions, Muranaka and the team are utilising numerical calculations. To overcome limitations associated with the analysis of spacecraft systems and plasma in space, the researchers perform analyses of objects under predetermined conditions without consideration of space or timescales. Although it isnâ–™t possible to fully replicate space conditions in ground-based vacuum chambers, in their analyses the researchers are able to obtain important raw measurement data on physical phenomena that have not been modelled, such as parameter measurements of electrically propelled plasma plumes. Through its research, the team hopes to contribute to spacecraft design by informing design parameters such as the spacecraft shape and thruster parameters. Ultimately, the researchers are expanding and verifying numerical models and developing advanced plasma interference analysis technologies that will prove invaluable to spacecraft design. The researchers’ investigations on the Hayabusa2 spacecraft’s side-cathode ion thruster system have yielded exciting results on the ion energy distribution function (IEDF) of backflowing ions at multiple points around this thruster, expanding their findings on the significance of thruster reference potential on ion energy distribution, which is key to understanding spacecraft surface erosion.

Research on the Friction Force Characteristics for the Double O-ring Seal of the Cylinder under the Small Displacement Condition

In order to obtain a high-precision pneumatic control system, it is necessary to study the friction force of the cylinder. However, few have considered the cylinder's frictional characteristics at small-displacements. This study investigated the influence of different conditions on the cylinder friction characteristics during the process from static to small-displacement of pneumatic double O-ring seal. A set of experimental apparatuses controlled by an electric actuator perform a seal ring small-displacement friction test to achieve the goals. The working principle of sealing rings in different deformation stages is expounded. According to experiments, the sealing ring's friction force in small-displacement movement can be separated into tilt, elastic deformation, pre-sliding, and sliding friction stages. Furthermore, the clearance characteristics between the sealing ring and the piston groove are verified, which decreases with the sealing ring thickness. Finally, the friction displacement characteristics of sealing rings under different pressures and materials during the elastic deformation stage were verified. It can be concluded that when the displacement is between 0.05-0.25mm, the friction of the sealing ring is almost linear with the displacement; when the displacement reaches 0.25mm, with the increase of the displacement, the friction force changes in a similar parabola manner. This study provides a detailed analysis of the friction characteristics of the seal in different stages of small displacement, which plays an important reference role in overcoming cylinder friction and promotes the development of pneumatic systems in the field of accurate position and speed control.

Selection of design parameters of a spacecraft electric propulsion engine ensuring the geostationary orbit raising mission

The problem of selecting suboptimal parameters of an electric propulsion system as part of a spacecraft, ensuring a geostationary orbit raising mission using a Soyuz-5 launch vehicle at the initial launch stage, is investigated. An expression is obtained for the main optimality criterion – the payload relative mass. An algorithm is obtained for solving the problem of parametric optimization of an electric propulsion system as part of a hybrid transportation system. The task of selecting the optimal electric propulsion engine for launching a spacecraft with an electric propulsion system to a geostationary orbit using the launch vehicle under consideration is solved. A design ballistic calculation and a comparative analysis of the obtained data are performed.

Fault Diagnosis Method for Marine Electric Propulsion Systems Based on Zero-Crossing Tacholess Order Tracking

In marine electric propulsion systems (MEPS) driven by variable-frequency drives, motor current signals often exhibit complex modulation components, ambiguous spectra, and severe noise interference, rendering it challenging to extract fault-related modulation components. To address this issue, we propose a zero-crossing tacholess order tracking method based on motor current signals. This method utilizes zero-crossing estimation of the instantaneous frequency to perform angular resampling of stator current signals and demodulates the envelope spectrum to extract fault characteristic spectra, enabling the diagnosis of mechanical faults in MEPS. Given the synchronization of the synchronous motor speed with the inverter fundamental frequency, this method estimates instantaneous frequencies in the time domain without requiring integration or time–frequency representation, which is simple and computationally efficient. Data validation on a small-scale marine electric propulsion test platform demonstrates that the proposed method exhibits good robustness under variable-speed conditions and effectively detects imbalance faults caused by propeller breakages and gear faults resulting from bevel gear tooth defects. Therefore, the proposed method can be applied to diagnose faults in downstream mechanical equipment driven by motors.

Paving the Way for Sustainable UAVs Using Distributed Propulsion and Solar-Powered Systems

Hybrid systems offer optimal solutions for unmanned aerial platforms, showcasing their technological development in parallel and series configurations and providing alternatives for future aircraft concepts. However, the limited energetic benefit of these configurations is primarily due to their weight, constituting one of the main constraints. Solar PV technology can provide an interesting enhancement to the autonomy of these systems. However, to create efficient propulsion architectures tailored for specific missions, a flexible framework is required. This work presents a methodology to assess hybrid solar-powered UAVs in distributed propulsion configurations through a two-level modeling scheme. The first stage consists of determining operational and design constraints through parametric models that estimate the baseline energetic requirements of flight. The second phase executes a nonlinear optimization algorithm tuned to find optimal propulsion configurations in terms of the degree of hybridization, number of propellers, different wing loadings, and the setup of electric distributed propulsion (eDP) considering fuel consumption as a key metric. The results of the study indicate that solar-hybrid configurations can theoretically achieve fuel savings of up to 80% compared to conventional configurations. This leads to a significant reduction in emissions during long-endurance flights where current battery technology is not yet capable of providing sustained flight.

Analysis of Impact of Control Strategies on Integrated Electric Propulsion System Performance During Icebreaking Process

Developing an efficient power system is an important way for icebreakers to respond to high maneuverability and strong fluctuation loads under icebreaking conditions. The performance of power systems under short-period, regularly fluctuating load-sea conditions has been intensively studied. However, the performance of the power system in the face of a long-period, stochastic multi-frequency fluctuation icebreaking process has not been fully explored, especially the parameter uncertainty and battery cycle life. In this study, an integrated electric propulsion system with an optimal control strategy is suggested for improving the power system’s dynamic performance and battery cycle life. First, an energy flow model with a diesel–electric unit as the main body and coupled energy storage system/hybrid energy storage system has been constructed. A comparative analysis of rule-based and optimization-based energy management strategies has been performed, and an optimized strategy with dynamic programming as global regulation at the upper level and model predictive control at the lower level is suggested to integrate the slow and fast dynamic powers and achieve adaptability to strong fluctuation loads. In this control strategy, the uncertainties of energy storage system/hybrid energy storage system parameters have been introduced to eliminate their impact on the system performance. Then, the icebreaking process with multi-frequency fluctuation has been simulated, and the hybrid energy storage system with battery and supercapacitor is recommended to reach multi-objective with the lowest power fluctuation of diesel–electric unit, highest efficiency, and the minimum battery degradation. Finally, the fuel oil consumption and emissions of the hybrid energy storage system have been discussed, and the optimized strategy can save fuel oil by up to 5.33% and reduce the CO2 emission by 22% during the icebreaking process, exhibiting great potential in the environmental friendliness and significant advantages in terms of low fuel oil consumption.

Optimization for fuel consumption and TCO of a heavy-duty truck with electricity-propelled trailer

As renewable energy grows in the heavy-duty truck sector, exploration of diverse solutions with varied energy types and powertrain configurations becomes a necessity. While most studies focus on powertrain configurations in tractors, this study takes a different approach: propose and evaluate new plug-in hybrid configurations with multiple power sources for heavy-duty trucks. The tractor retains its engine powertrain, while the trailer is equipped with electric axle(s), forming a fuel-electricity hybrid propulsion system. The specifications of the electric propulsion system are optimized, using a multi-objective particle swarm optimization algorithm and dynamic programming control algorithm to evaluate the energy consumption and total cost of ownership (TCO). The results highlight the potential of the configuration with three electric axles and single reduction gear in regard to vehicle energy consumption. Conversely, the configuration with one electric axle and a two-speed transmission exhibits the lowest TCO. Under the China World Transient Vehicle Cycle, the fuel consumption of the diesel truck is reduced by up to 44.59 % with the use of the optimized hybrid configuration. The truck's TCO can be then reduced by up to 832 thousand CNY in one-million-kilometer operation. For an actual road operation, these figures change to 34.79 % and 284 thousand CNY, respectively.

Electro-mobility – an Opportunity to Develop a More Sustainable Transport System

The future of transport is electro-mobility, a technology that ensures environmentally friendly and energy efficient vehicles on the road. But to exploit the full benefits of electric propulsion there are still many challenges to overcome. These challenges are related to the cost and residual value (aftermarket) of the vehicles, battery life and cost, charging and range. This article discusses these challenges as well as the state of the electric vehicle market. The aim is to present to what extent the development of electric mobility in Europe and in Bulgaria will outline a more sustainable transport system and to outline what the opportunities for its development are. Decarburization of transport is key to achieving sustainable mobility ensuring transport connectivity across the continent.

Development of Self-Powered Prosthetic Finger with Pneumatic Passive Joints for Distal Interphalangeal Joint Amputees

Myoelectric prosthetic hands and fingers with grasping functions have challenges such as weight, cost, and grasping performance of flexible objects owing to the use of electric actuators. To resolve these problems, we propose a self-powered movable prosthetic finger using pneumatic pressure. This prosthetic finger utilizes the flexion/extension of the remaining finger of the user to drive a wire and flex or extend the finger joints. The use of a tendon (wire) and belt drives reduces the space occupied by the prosthetic finger unit compared with conventional linked prosthetic fingers. Furthermore, a sealed-air bellows is used for the joint for flexible grasping owing to passive variable-compliance and damping, which is impossible with only a tendon drive. These features have resulted in the stable grasping of various objects that are difficult to grasp using prosthetic fingers based on conventional technologies.

Assessing the Impact of Hybrid Propulsion Systems on the Range and Efficiency of Aircraft

The demand for aviation continues to grow, posing issues in terms of fuel consumption, environmental effect, and operational efficiency. In addition, the COVID-19 pandemic has also highlighted the need for sustainable solutions in the aviation sector. To address these issues, hybrid electric propulsion systems have emerged as a potential option. Hybrid electric propulsion systems have the potential to improve airplane performance while reducing environmental impact. This article looks into the effects of hybrid electric propulsion technologies on optimal aircraft range. The study looks at aviation's environmental impact, several hybrid aircraft prototypes, and battery capacity and density challenges. Fuel usage increases in proportion to the weight of the aircraft. As a result, the range is shorter. In modern technology, along with to the added weight of batteries used as energy storage in hybrid propulsion systems, there are low battery densities and capacities. When the researches were reviewed, it was discovered that overcoming these limitations was easier for small aircraft and more difficult for large aircraft. As a consequence of the studies and research conducted, the development of light and reliable batteries with high energy density and capacity would expand the range of hybrid aircraft and allow them to be used more efficiently over long distances.

Digital twins for electric propulsion technologies

As the space industry is undergoing an evolution, the current approaches toward design, development, and qualification of Electric Propulsion (EP) systems largely based on empirical “trial-and-error” methodologies are falling short of addressing the emerging needs and keeping abreast of the rapid changes in market trends. Furthermore, with the proliferation of Artificial Intelligence (AI) within the space industry toward next-generation autonomous satellites and spacecrafts, the conventional EP monitoring and control strategies become inadequate and need to give way to approaches compatible with satellite-level autonomy requirements. A digital twin (DT) – a technology capable of providing an accurate dynamically adapting virtual representation of a physical asset – is a game-changing concept that catalyzes the transcendence of the EP industry past its pressing challenges today. In this paper, we aim to: (i) define the DT concept, highlighting how it surpasses traditional modelling, (ii) enumerate the DT’s breakthrough promises for the EP industry, and (iii) specify the challenges to realize practical and scalable EP DTs. Additionally, we report on the technical progress achieved and/or planned at Imperial Plasma Propulsion Laboratory to fill the foundational gaps in three building block elements of DTs, namely, (i) a cost-effective kinetic model to generate extensive high-fidelity databases for machine learning (ML), (ii) ML-enabled models for prediction and analysis of performance and operational behavior, and (iii) a DT architecture that integrates the numerical models in terms of a computing infrastructure and provides data pipelines and interfaces for the DT’s data exchanges with the real world, its dynamic updating, and uncertainty quantification.

A Validated Unsteady Turbofan Engine Performance Simulation Using Pseudo Bond Graph Approach

Abstract In this paper, the unsteady performance of a turbofan engine is illustrated and modeled using the pseudo-bond graph approach. The pseudo-bond graph method allows multiphysical and interdisciplinary systems to be described analytically and comprehensibly across disciplines. In this study, a high bypass ratio turbofan engine is modeled using a pseudo-bond graph model that can be adapted for hybrid electric propulsion systems. The development of the model is followed by a full-scale test run of the in-house V2500-A1 turbofan engine. The highly instrumented turbofan engine enables the time-resolved recording of performance-specific variables, thus facilitating the validation of the numerical model. Slam acceleration and deceleration are performed to analyze the unsteady performance. It is shown that the pseudo-bond graph model is able to predict the dynamics of the turbofan engine. High deviations are explained by the incomplete modeling of the control system.

In Operando Health Monitoring for Lithium-Ion Batteries in Electric Propulsion Using Deep Learning

Battery management systems (BMSs) play a vital role in understanding battery performance under extreme conditions such as high C-rate testing, where rapid charge or discharge is applied to batteries. This study presents a novel BMS tailored for continuous monitoring, transmission, and storage of essential parameters such as voltage, current, and temperature in an NCA 18650 4S lithium-ion battery (LIB) pack during high C-rate testing. By incorporating deep learning, our BMS monitors external battery parameters and predicts LIB’s health in terms of discharge capacity. Two experiments were conducted: a static experiment to validate the functionality of BMS, and an in operando experiment on an electrically propelled vehicle to assess real-world performance under high C-rate abuse testing with vibration. It was found that the external surface temperatures peaked at 55 °C during in operando flight, which was higher than that during static testing. During testing, the deep learning capacity estimation algorithm detected a mean capacity deviation of 0.04 Ah, showing an accurate state of health (SOH) by predicting the capacity of the battery. Our BMS demonstrated effective data collection and predictive capabilities, mirroring real-world conditions during abuse testing.

Fuzzy Logic-Based Energy Management Strategy for Hybrid Fuel Cell Electric Ship Power and Propulsion System

The growing use of proton-exchange membrane fuel cells (PEMFCs) in hybrid propulsion systems is aimed at replacing traditional internal combustion engines and reducing greenhouse gas emissions. Effective power distribution between the fuel cell and the energy storage system (ESS) is crucial and has led to a growing emphasis on developing energy management systems (EMSs) to efficiently implement this integration. To address this goal, this study examines the performance of a fuzzy logic rule-based strategy for a hybrid fuel cell propulsion system in a small hydrogen-powered passenger vessel. The primary objective is to optimize fuel efficiency, with particular attention on reducing hydrogen consumption. The analysis is carried out under typical operating conditions encountered during a river trip. Comparisons between the proposed strategy with other approaches—control based, optimization based, and deterministic rule based—are conducted to verify the effectiveness of the proposed strategy. Simulation results indicated that the EMS based on fuzzy logic mechanisms was the most successful in reducing fuel consumption. The superior performance of this method stems from its ability to adaptively manage power distribution between the fuel cell and energy storage systems.

Research on Large Hybrid Electric Aircraft Based on Battery and Turbine-Electric

Hybrid electric aircraft use traditional engine and electric propulsion combinations to optimize aircraft architecture, improve propulsion efficiency, and reduce fuel consumption. As a new technology, the fuel and energy consumption calculation of hybrid electric aircraft is more complicated than traditional aircraft due to the usage of different energy forms. The purpose of this paper is to develop the analytical method for fuel and energy consumption for hybrid electric aircraft. This paper summarizes the working principle of hybrid electric aircraft, including the system architecture and power conversion mechanism. The calculation of fuel and energy consumption for hybrid electric aircraft is carried out in detail. In order to evaluate large hybrid electric aircraft, the architecture, based on energy flow, is established, and turbofan engine, electrical system, electric duct fan, and aerodynamic model characteristics are established. With a single-aisle aircraft as an example, the fuel and energy consumption under the 800 nautical mile range is performed. It shows that fuel consumption can be reduced by 10% and energy consumption by 4.7% compared with a traditional aircraft. The effects of different range and battery ratios are analyzed. The payload range for the hybrid electric aircraft is analyzed. The results show that even though the hybrid electric aircraft reduces the payload and range, it can significantly reduce fuel and energy consumption.

Modeling and numerical analysis of Kangaroo lower body based on constrained dynamics of hybrid serial–parallel floating-base systems

This paper presents the modeling and numerical analysis of the Kangaroo lower body prototype, a novel bipedal humanoid robot developed and manufactured by PAL Robotics. Kangaroo features high-power linear electric actuators combined with unique serial–parallel hybrid chains, which allow for the positioning of all the leg actuators near the base of the robot to improve the overall mass distribution. To model and analyze such complex nonlinear mechanisms, we employ a constrained formulation that is extended to account for floating-base systems in contact with the environment. A comparison is made to demonstrate the significant improvements achieved with TALOS, another humanoid bipedal robot designed by PAL Robotics, in terms of equivalent Cartesian inertia at the feet and centroidal angular momentum. Finally, the paper includes numerical experiments conducted through simulation and preliminary tests performed on the actual Kangaroo platform.

Reproducibility of operating potentials for a C12A7 electride plasma-based cathode with constant keeper current control

Hollow Cathodes are fundamental components for electric propulsion systems. In recent publications, the performance of a planar C12A7 electride cathode has been presented with promising results. This includes the endurance operation of the cathode, the heaterless ignition cycling, and the general performance mapping over a wide range of parameters. The present publication will add to these publications, presenting results of only one defined set of discharge parameters, allowing a statistical evaluation of repeated discharge operations. Overall, exceptable repeatability of the performance could be evaluated, confirming the overall performance trends observed in previous campaigns. The cathode was operated in self-heating mode using krypton as propellant in a current range of 100 mA to 600 mA. A discharge potential of 30 V with a slight increase for lower discharge currents is reported. Furthermore, means to reduce the variation in the test results by increasing the keeper current have been identified.

Thermodynamic behavior of high-power inductively coupled plasma quartz tube wall

High-power inductively coupled plasmas are commonly used in planetary entry simulations and are increasingly being used in electric propulsion applications. However, during the operation of the system, the walls of the quartz tube will crack and melt. Its thermodynamic behavior is key to ensuring the safe and reliable operation of the system, which is directly related to the distribution of thermal energy within the discharge volume. In this paper, the temperature and stress distribution of the quartz tube wall of an inductively coupled plasma generator at 27 kW–85 kW are described. A numerical simulation model was established to depict the interaction between the plasma and the quartz tube wall. In the field of experimental research, the temperature of the outer wall of the quartz tube was obtained by using a thermal imager, and a non-uniform B-spline difference method was proposed to fit the outer wall temperature of the quartz tube to eliminate the influence of the induction coil. It is found that the numerical simulation and experimental results show that the temperature is stable region, temperature rise area, temperature drop zone, and the high temperature region of the quartz tube wall is located in the coil area, and the high stress area is also located in this region. On this basis, the outer wall temperature and thermal stress of quartz tubes under different heat fluxes are studied. When the heat flux exceeds 18.6 kW/m2, the stresses in the coil area and downstream of the coil exceed the limit stress. Mechanical failures may occur in areas where the ultimate stresses are exceeded, and these results can provide theoretical data for the optimal design of high-power inductively coupled plasma generators.

Inclined Installation Effect on the Offset Strip Finned Heat Exchanger Designed for a Hybrid Electric Propulsion System in Electric Vertical Take-Off and Landing

The plate-fin heat exchanger was designed for the liquid cooling thermal management system of the hybrid electric propulsion system for an electric vertical take-off and landing (eVTOL) vehicle. The offset-strip fin design was applied, and the performance of the heat exchanger was evaluated, particularly with respect to the inclination of the airflow entering the heat exchanger. The estimated performance during the design phase matched well with the experimental results. The inclination of the heat exchanger had a minimal effect on thermal performance, with a slight increase in performance as the inclination increased. However, the pressure difference along the airflow was affected, likely increasing as the inclination increased. The sensitivity of various parameters on coolant temperature was also investigated. The air inlet temperature had a significant effect on coolant temperature, followed by the coolant flow rate. Therefore, when designing the thermal management system, careful consideration should be given to the ambient air temperature and coolant flow rate.

Analysis and prediction of sputtering yield using combined hierarchical clustering analysis and artificial neural network algorithms

Sputtering is a crucial technology in fields such as electric propulsion, materials processing and semiconductors. Modeling of sputtering is significant for improving thruster design and designing material processing control algorithms. In this study we use the hierarchical clustering analysis algorithm to perform cluster analysis on 17 descriptors related to sputtering. These descriptors are divided into four fundamental groups, with representative descriptors being the mass of the incident ion, the formation energy of the incident ion, the mass of the target and the formation energy of the target. We further discuss the possible physical processes and significance involved in the classification process, including cascade collisions, energy transfer and other processes. Finally, based on the analysis of the above descriptors, several neural network models are constructed for the regression of sputtering threshold E th, maximum sputtering energy E max and maximum sputtering yield SY max. In the regression model based on 267 samples, the four descriptor attributes showed higher accuracy than the 17 descriptors (R 2 evaluation) in the same neural network structure, with the 5×5 neural network structure achieving the highest accuracy, having an R 2 of 0.92. Additionally, simple sputtering test data also demonstrated the generalization ability of the 5×5 neural network model, the error in maximum sputtering yield being less than 5%.