Search Results (115)

The hydraulically driven piston compressor is a state-of-the-art solution for compressing hydrogen to pressure levels up to 100 MPa and even beyond, especially for use in hydrogen refueling stations. Based on the technical data of a few commercial hydraulically driven piston systems for hydrogen compression, thermodynamic calculations are developed in this paper, and a preliminary indicator, the compression-to-electric power ratio (CEPR), is assessed. In order to justify calculated CEPR values no greater than 0.42 for the analyzed compression units, attention is paid to the hydrogen compression duty, and the instantaneous power is drawn based on a simple but effective procedure. In detail, the instantaneous power profile has a peak value approximately double that of the average power, and this peak is maintained for almost half of the working period. According to this result, the electric motor must be sized correctly. Thus, it might seem over-configured if compared to the average compression power, hence the relatively low CEPR values. Finally, in order to support the current assessment of the instantaneous power, considerations about the control system for piston movement inversion are reported. Full article

This study introduces a review on high-speed electrical motors (HSEMs) used for fuel cell (FC) compressor systems, to feed air into the FC stack. This technology is designed for electric vehicle (EV) applications. First, an evaluation of electrical machines as the main energy consumers of EVs is conducted to situate the current study in terms of the mechanical characteristics. Next, the main electrical motor configurations found in the scientific literature, and suitable for applications in FC compressor systems, are presented. Three case studies are depicted to identify the main challenges of this application in terms of the mechanical robustness and efficiency. Finally, a perspective on improving the energetic performance of HSEMs is presented, in terms of the materials used, the shape of the geometry, the winding type and insulation, the cooling, and the optimization techniques used to maximize the performance of HSEMs. Full article

Switched reluctance motors (SRMs) are promising for applications such as air compressors due to their robust structure and fault tolerance, but suffer from high torque ripple and radial electromagnetic forces that cause vibration and noise. This paper proposes a game-theoretic multi-objective design optimization framework to enhance electromagnetic performance by simultaneously maximizing average torque and minimizing radial force. The optimization problem is transformed into a game model where objectives are treated as players with strategy spaces derived through fuzzy clustering and correlation analysis. Particle swarm optimization (PSO) is employed to solve the payoff functions under both novel cooperative and non-cooperative game scenarios of SRMs’ structural design. Finite element analysis (FEA) validates the optimized motor topology, showing that the cooperative game model achieves a balanced performance with high torque density and reduced vibration, meeting the requirements for air compressor drives. The proposed method effectively resolves the weight selection challenge in traditional multi-objective optimization and demonstrates strong engineering feasibility. Full article

Various compressors found in appliances such as air conditioners, refrigerators, dehumidifiers, etc., are gaining more popularity in different areas, including industry, retail, consumer electronics, and others. This market is growing fast, attracting numerous manufacturers who are closely competing with each other. Simultaneously, the requirements for compressor drive efficiency and for reducing their carbon footprint are becoming tougher, which is prompting manufacturers to pay serious attention to this problem. Compressor drives operate in many modes, and almost all of them have been studied and optimized. The exception to this is the preheating mode, which is required to warm the lubricating oil before beginning compressor operations. This mode is rarely used in warm climates; therefore, previous researchers have ignored it. However, with the spread of compressor applications into countries with colder climates, the significance of the preheating mode has increased. This study examines the preheating mode of compressor drives and proposes several techniques that increase their efficiency by 4.15% and decrease the preheating time by 3.6 times. Furthermore, the author developed an algorithm that makes the load to the inverter and motor phases more even, thus increasing the lifespan of compressors and reducing their carbon footprint. Full article

This paper presents a comprehensive sensorless control approach for interior permanent magnet (IPM) motors, integrating high-frequency injection (HFI) and model-based observer techniques to ensure accurate rotor position estimation across a wide speed range. Two HFI strategies—pulsating and rotating—are investigated experimentally and compared in combination with two observer structures: the conventional Sliding Mode Observer (SMO) and Adaptive-Gain SMO (AG-SMO). The AG-SMO dynamically adjusts its observer gain according to the estimated back-electromotive force (back-EMF) amplitude, significantly reducing chattering and improving estimation performance under varying load and noise conditions. A Frequency-Adaptive Complex Coefficient Filter (FACCF) and an Orthogonal Phase-Locked Loop (PLL) are incorporated to eliminate phase delay and enhance demodulation accuracy. Simulation and experimental results obtained using a 30 W, 20 V IPM motor demonstrate that the pulsating HFI + AG-SMO configuration achieves superior stability and noise immunity, while the rotating HFI + AG-SMO provides smoother and more accurate estimation. Overall, the proposed hybrid control framework achieves robust, high-precision, and sensorless operation for IPM motors over the wide speed range, offering a practical solution for applications such as inverter-driven compressor systems operating in noisy environments. Full article

Hybrid Gas–Magnetic Bearings (HGMBs) are an emerging technology ready to completely change high-speed oil-free rotor support in aerospace electric motors. Because HGMBs combine the stiffness and load capacity of gas bearings with the active control of magnetic bearings, enabling oil-free, contactless rotor support from zero to ultra-high speeds. They offer more load capacity of standalone magnetic bearings while maintaining full levitation across the entire speed range. Dual-mode operation, magnetic at low speeds and gas film at high speeds, minimizes control power and thermal losses, making HGMBs ideal for high-speed aerospace systems such as cryogenic turbopumps, electric propulsion units, and hydrogen compressors. While not universally optimal, HGMBs excel where extreme speed, high load, and stringent efficiency requirements converge. Advances in modeling, control, and manufacturing are expected to accelerate their adoption, marking a shift toward hybrid electromagnetic–aerodynamic rotor support for next-generation aerospace propulsion. This review provides a thorough overview of emerging HGMBs, emphasizing their design principles, performance metrics, application case studies, and comparative advantages over conventional gas or magnetic bearings. We include both a historical perspective and the latest developments, supported by technical data, experimental results, and insights from recent literature. We also present a comparative discussion including future research directions for HGMBs in aerospace electrical machine applications. Full article

This study presents a streamlined and accurate approach for modeling the performance of hermetic reciprocating compressors under variable-speed conditions. Traditional compressor models often neglect the influence of motor frequency, leading to considerable deviations at low-speed operation. To address these limitations, a frequency-dependent numerical framework was developed using one-dimensional (1-D) and two-dimensional (2-D) polynomial regressions to represent volumetric efficiency (${\eta }_v$) and isentropic efficiency (${\eta }_{isentr}$) as functions of compression ratio (r) and motor speed frequency (f). The proposed model integrates manufacturer data and thermodynamic property databases to predict compressor behavior across a wide range of operating conditions. Validation using the Bitzer 4HTE-20K CO₂ compressor demonstrated strong agreement with experimental data, maintaining prediction errors within ±10% for both power input and discharge temperature. Moreover, the model enhanced accuracy by up to 19.4% in the low-frequency range below 40 Hz, where conventional models typically fail. The proposed method provides a practical and computationally efficient tool for accurately simulating the performance of hermetic reciprocating compressors that support improved design, optimization, and control of refrigeration and heat pump systems. Full article

This paper presents a sensorless control strategy for permanent magnet synchronous motor (PMSM) drives in industrial and automotive air compressor applications. The strategy utilizes an adaptive-gain sliding mode observer integrated with a refined back-EMF model to suppress chattering and improve convergence. The proposed approach achieves precise rotor position and speed estimation across a wide operational range without mechanical sensors. It directly addresses the critical needs of reliability, compactness, and resilience in automotive environments. Unlike conventional observers, its originality lies in the enhanced gain structure, enabling accurate and robust sensorless control validated through both simulation and hardware tests. Comprehensive simulation results demonstrate effective performance from 2000 to 8500 rpm, with steady-state speed tracking errors maintained below 0.4% at 2000 rpm and 0.035% at 8500 rpm under rated load. The control methodology exhibits excellent disturbance rejection capabilities, maintaining speed regulation within ±5 rpm under an 80% load disturbance at 8500 rpm while limiting q-axis current ripple to 2.5% of rated values. Experimental validation on a 2.2 kW PMSM-driven compressor test platform confirms stable operation at 4000 rpm with speed fluctuations constrained to 20 rpm (0.5% error) and precise current regulation, maintaining the d-axis current within ±0.07 A. The system demonstrates rapid dynamic response, achieving acceleration from 1320 rpm to 2365 rpm within one second during testing. The results confirm the method’s practical viability for enhancing reliability and reducing maintenance in industrial and automotive compressors systems. Full article

Shell-like housing structures for motors and compressors can be found in everyday products. Consumers significantly evaluate acoustic emissions during the first usage of products. Unpleasant sounds may raise concerns and cause complaints to be issued. A prevention strategy is a holistic acoustic design, which includes predicting the emitted sound power as part of end-of-line testing. The hybrid experimental-simulative sound power prediction based on laser scanning vibrometry (LSV) is ideal in acoustically harsh production environments. However, conducting vibroacoustic testing with laser scanning vibrometry is time-consuming, making it difficult to fit into the production cycle time. This contribution discusses how the time-consuming sampling process can be accelerated to estimate the radiated sound power, utilizing adaptive sampling. The goal is to predict the acoustic signature and its uncertainty from surface velocity data in seconds. Fulfilling this goal will enable integration into a product assembly unit and final acoustic quality control without the need for an acoustic chamber. The Gaussian process regression based on PyTorch 2.6.0 performed 60 times faster than the preliminary reference implementation, resulting in a regression estimation time of approximately one second for each frequency bin. In combination with the Equivalent Radiated Power prediction of the sound power, a statistical measure is available, indicating how the uncertainty of a limited number of surface velocity measurement points leads to predictions of the uncertainty inside the acoustical signal. An adaptive sampling algorithm reduces the prediction uncertainty in real-time during measurement. The method enables on-the-fly error analysis in production, assessing the risk of violating agreed-upon acoustic sound power thresholds, and thus provides valuable feedback to the product design units. Full article

This study evaluates the energy performance of a BOGE C 22-2 oil-injected rotary screw compressor under real industrial conditions. Using direct measurements with a power quality analyzer and thermodynamic modeling, key performance indicators such as compression work, mass flow rate, compressor efficiency, and motor efficiency were determined. The results revealed actual efficiencies of 27–48%, significantly lower than the expected 60–70% for this type of equipment, mainly due to partial-load operation and low airflow demand. A low power factor of approximately 0.72 was also observed, caused by a high share of reactive power consumption. To address these inefficiencies, the study recommends the installation of an automatic capacitor bank to improve power quality and the integration of a secondary variable speed compressor to enhance performance under low-demand conditions. These findings underscore the importance of assessing compressor behavior in real-world environments and implementing techno-economic strategies to increase energy efficiency and reduce industrial electricity consumption. Full article

This study focuses on improving the efficiency of interior permanent magnet synchronous motors (IPMSMs) for electric vehicle (EV) compressors. Seven rotor topologies (B, dB, V, dV, D, U, and UV) were first compared, among which the U-type rotor demonstrated the highest efficiency and the lowest total loss. Subsequently, the influence of the turn number and rotor outer diameter (ROD) on the shift of the high-efficiency region was analyzed, and six key design variables were identified through Pearson correlation-based sensitivity analysis. Using these variables, a multi-objective optimization was performed in Ansys OptiSLang, which improved the integrated part load value (IPLV)-weighted efficiency from 91.05% to 92.29% and shifted the high-efficiency region closer to the main operating point. Experimental validation of the reference model confirmed the reliability of the FEM analysis, and the proposed optimal design is expected to enhance low-speed efficiency and reduce battery energy consumption in EV compressor applications. Full article

This work presents the results of a research study focused on the development and evaluation of an algorithmic optimal control framework for energy-efficient operation of screw compressors in smart power systems. The proposed approach is based on the Pontryagin maximum principle (PMP), which enables the synthesis of a mathematically grounded regulator that minimizes the total energy consumption of a nonlinear electromechanical system composed of a screw compressor and a variable-frequency induction motor. Unlike conventional PID controllers, the developed algorithm explicitly incorporates system constraints, nonlinear dynamics, and performance trade-offs into the control law, allowing for improved adaptability and energy-aware operation. Simulation results obtained using MATLAB/Simulink confirm that the PMP-based regulator outperforms classical PID solutions in both transient and steady-state regimes. Experimental tests conducted in accordance with standard energy consumption evaluation methods showed that the proposed PMP-based controller provides a reduction in specific energy consumption of up to 18% under dynamic load conditions compared to a well-tuned basic PID controller, while maintaining high control accuracy, faster settling, and complete suppression of overshoot under external disturbances. The control system demonstrates robustness to parametric uncertainty and load variability, maintaining a statistical pressure error below 0.2%. The regulator’s structure is compatible with real-time execution on industrial programmable logic controllers (PLCs), supporting integration into intelligent automation systems and smart grid infrastructures. The discrete-time PLC implementation of the regulator requires only 10³ arithmetic operations per cycle and less than 10² kB of RAM for state, buffers, and logging, making it suitable for mid-range industrial controllers under 2–10 ms task cycles. Fault-tolerance is ensured via range and rate-of-change checks, residual-based plausibility tests, and safe fallbacks (baseline PID or torque-limited speed hold) in case of sensor faults. Furthermore, the proposed approach lays the groundwork for hybrid extensions combining model-based control with AI-driven optimization and learning mechanisms, including reinforcement learning, surrogate modeling, and digital twins. These enhancements open pathways toward predictive, self-adaptive compressor control with embedded energy optimization. The research outcomes contribute to the broader field of algorithmic control in power electronics, offering a scalable and analytically justified alternative to heuristic and empirical tuning approaches commonly used in industry. The results highlight the potential of advanced control algorithms to enhance the efficiency, stability, and intelligence of energy-intensive components within the context of Industry 4.0 and sustainable energy systems. Full article

This paper presents the design of a permanent-magnet-assisted synchronous reluctance motor (PMa-SynRM) for compressor applications using Sm-series injection-molded magnets that eliminate heavy rare-earth elements. The high shape flexibility of the injection-molded magnets enables the formation of a curved multi-layer flux-barrier rotor geometry based on the Joukowski airfoil potential, optimizing magnetic flux flow under typical compressor operating conditions. Furthermore, electromagnetic performance, irreversible demagnetization behavior, and rotor stress sensitivity were analyzed with respect to key design variables to derive a model that satisfies the target performance requirements. The validity of the proposed design was confirmed through finite element method (FEM) comparisons with a conventional IPMSM using sintered NdFeB magnets, demonstrating the feasibility of HRE-free PMa-SynRM for high-performance compressor drives. Full article

The permanent magnetic synchronous motor (PMSM) is of significant use for the centrifugal hydrogen compressor (CHC) in the hydrogen fuel cell system. In order to satisfy the demand for improving the CHC’s performance, including higher accuracy, higher response speed, and wider speed range, this paper proposes a novel adaptive super-twisting sliding mode observer (ASTSMO)-based position sensorless control strategy for the highspeed PMSM. Firstly, the super-twisting algorithm (STA) is introduced to the sliding mode observer (SMO) to reduce chattering and improve the accuracy of position estimation. Secondly, to increase the convergence speed, the ASTSMO is extended with a linear correction term, where an extra proportionality coefficient is used to adjust the stator current error under dynamic operation. Finally, a novel adaptive law is designed to solve the PMSM’s problems of wide speed change, wide current variation, and inevitable parameters fluctuation, which are caused by the CHC’s complex working environment like frequent load changes and significant temperature variations. In the experimental verification, the position accuracy and dynamic performance of the PMSM are both improved. It is also proved that the proposed strategy can guarantee the stable operation and fast response of the CHC, so as to maintain the reliability and the hydrogen utilization of the hydrogen fuel cell system. Full article

Large synchronous motors are typically used to drive various load equipment, such as reciprocating compressors. Due to the continuous oscillation of the load, the pulsating torque acting on the main shaft of the synchronous motor will continuously vary with the load changes. This leads to forced oscillations during the dynamic stable operation of the unit, subsequently causing severe problems such as overheating, noise, and failures. Moreover, the rotor length of large synchronous motors is generally greater than the rotor diameter, giving the rotor certain flexible characteristics. During a motor’s operation, it is necessary to cross the first-order critical speed, making resonance highly likely to occur. Therefore, the analysis of dynamic characteristics of large synchronous motors is particularly important. This study investigates the dynamic characteristics of a 7800 kW-18P large synchronous motor rotor system through comprehensive theoretical and experimental analyses. The research encompasses three key aspects: (1) modal analysis comparing fan-equipped and fan-free configurations, (2) harmonic response evaluation, and (3) critical speed determination under concentrated mass conditions. Experimental validation was performed via impact hammer testing, with measured natural frequencies showing a strong correlation with simulated results for the magnetic pole core assembly. The findings not only confirm the operational speed validity but also establish a reliable foundation for the subsequent structural optimization of high-power synchronous machines. Full article