Motor Noise Research Articles

Acoustic analysis of a three-dimensional cylindrical shell model under electromagnetic vibration

This paper presents the acoustic analysis of a three-dimensional cylindrical shell model under electromagnetic vibration, a critical factor affecting the performance of electric motors in various applications such as automotive, aerospace, and industrial systems. The study provides a multidisciplinary approach that integrates electromagnetics, structural vibration, and acoustics, solved using the fast multipole boundary element method (FMBEM). The results summarize the validation of the analytical models and numerical simulations, offering insights into effective vibration reduction methods. The conclusions indicate that the 3-D numerical analysis using FMBEM aligns well with the analytical solution for the sound pressure in the exterior acoustic domain of the cylindrical shell model. The paper contributes valuable insights for the design of low-noise motors and the control of electromagnetic vibration and noise in electric motors.

Improving the Dynamics of an Electrical Drive Using a Modified Controller Structure Accompanied by Delayed Inputs

This paper presents the operation of a modified speed controller with a standard PI/PID structure that includes the preprocessing of the controller’s input signal, focusing on the past behavior of control errors. The modification involves adding a delay line, with the outputs of the individual line segments summed with a weighting method, as detailed in the paper. One of the significant advantages of this method is its use of a standard industrial controller structure, which makes it highly practical and easily implementable in existing systems. By relying on well-established control frameworks, this approach reduces the need for specialized hardware or complex modifications, allowing for smoother integration and lower implementation costs. The delay-based signal shaping shows excellent properties for the electric drive system powered by a hard-switching PWM converter. The set of weighted delays acts as a filter whose parameters are chosen using the quality function to test different configurations for optimal performance. When tested in a speed control system for a Permanent Magnet Synchronous Motor, the modifications improved the control quality index, indicating better performance and efficiency. Importantly, the system allows for reducing or eliminating the gain in the differentiating part of the controller, which decreases motor current chattering and noise. This paper includes an experimental verification of the proposed solution in a laboratory setting under semi-industrial conditions.

Enhancing vibroacoustic reduced order models for digital twin development in industrial applications

In recent years, the growing interest towards the Digital Twin has prompted extensive exploration in both academic and industrial domains. To realize this technology, the development of simulation models that seamlessly run parallel to the physical assets is necessary. Model Order Reduction (MOR) plays a pivotal role, significantly easing the computational demands of 3D models while maintaining high fidelity. Krylov-based methods have proven successful in various vibroacoustic applications. However, state-of-the-art contributions employ suboptimal modeling strategies, leading to computationally inefficient offline phases and limited scalability. The linear Finite Element Method (FEM) exhibits lower efficiency than high-order FEM; Astley-Leis infinite elements, used to enforce non-reflecting conditions, constrain models to spherical domains, proving inefficient for elongated structures. In this work, advanced techniques-FEM Adaptive Order (FEMAO) and flexible infinite elements- are employed to alleviate the computational burden of the MOR process. The advantages of combining MOR, FEMAO, and flexible infinite elements are explored through various numerical examples. Specifically, we highlight the efficiency of output-based MOR in handling models with a high number of inputs, showcasing practical applications, especially in electric motor noise analysis. In conclusion, these numerical techniques reduce the computational burden of the offline phase, unlocking the Digital Twin for large-scale industrial models.

Sound quality improvement technique for inverter-driven motors

Motor-driven products are becoming increasingly popular along with the trend toward carbon neutrality. Motor units driven by PMW inverters are one of the key components of motor-driven products, but since they are also one of the dominant sound sources, there are high demands for quietness, including sound quality improvement, in terms of comfort. During the DC-AC conversion process, the PWM inverter generates harmonic current distortions and, moreover, the electromagnetic excitation forces generated in the air gap between the rotor and stator induce harmonic vibrations in the motor. Therefore, this presentation describes the mechanism of motor noise generation from the excitation source to propagation and radiation, and activities to improve sound quality for the motor unit driven by inverters.

Low Vibration Control Scheme for Permanent Magnet Motor Based on Resonance Controllers

For an electric locomotive traction motor, it is necessary to maintain relatively low vibration and noise due to the higher design standards. By using effective motor control strategies and implementing current harmonic suppression schemes, motor efficiency and vibration and noise suppression can be effectively improved. This study investigates the current harmonic suppression strategy for permanent magnet synchronous motors by (1) constructing a mathematical model of the permanent magnet motor to explore the sources of low-order harmonics currents such as fifth and seventh harmonics, as well as high-order harmonics at switch frequencies and their multiples, and analyzing the electromagnetic force characteristics generated by the current, and (2) establishing a vector control system for the permanent magnet motor. To suppress the fifth and seventh harmonic components in the current, a resonance controller is constructed, which utilizes the parallel connection of a resonator and PI controller to achieve low-order harmonic suppression. The factors affecting the effectiveness of the resonance controller’s suppression are also analyzed. The experiments are conducted, and the current harmonic suppression scheme constructed in this study can effectively reduce the harmonics in the current, thereby reducing motor vibration and noise.

M3D‐DPWM strategy for three‐phase four‐leg inverter with higher harmonic suppression capability

AbstractThree‐phase four‐leg inverters are widely used in power systems due to their inherent ability to handle unbalanced loads. However, with conventional 3D space vector pulse width modulation (3D‐SVPWM), high harmonics of large amplitude exist in the output voltage around the switching frequency and its integer multiples leading to noise in the load motor and limiting the application range of the inverter system. The passband amplification of conventional sinusoidal filters and their cutoff frequency vary with the load, so it is particularly important to investigate the regulation strategy with harmonic suppression. In this study, an improved 3D discontinuous pulse width modulation (M3D‐DPWM) strategy is proposed based on 3D‐SVPWM. By reducing the conventional 3D‐SVPWM switching segments and changing the vector synthesis sequence of the last half switching cycle, the output phase voltage period is reduced to half of the original one, which achieves the purpose of suppressing the output voltage at the switching frequency and its odd multiple high harmonics without changing the fundamental characteristics and adding additional circuits. In contrast, the conventional 3D‐SVPWM switching frequency is increased to 20 kHz to achieve similar performance. Finally, the effectiveness of the proposed strategy is verified by simulation and experiment.

Enhanced motor noise in an autism subtype with poor motor skills

BackgroundMotor difficulties are common in many, but not all, autistic individuals. These difficulties can co-occur with other problems, such as delays in language, intellectual, and adaptive functioning. Biological mechanisms underpinning such difficulties are less well understood. Poor motor skills tend to be more common in individuals carrying highly penetrant rare genetic mutations. Such mechanisms may have downstream consequences of altering neurophysiological excitation-inhibition balance and lead to enhanced behavioral motor noise.MethodsThis study combined publicly available and in-house datasets of autistic (n = 156), typically-developing (TD, n = 149), and developmental coordination disorder (DCD, n = 23) children (age 3–16 years). Autism motor subtypes were identified based on patterns of motor abilities measured from the Movement Assessment Battery for Children 2nd edition. Stability-based relative clustering validation was used to identify autism motor subtypes and evaluate generalization accuracy in held-out data. Autism motor subtypes were tested for differences in motor noise, operationalized as the degree of dissimilarity between repeated motor kinematic trajectories recorded during a simple reach-to-drop task.ResultsRelatively ‘high’ (n = 87) versus ‘low’ (n = 69) autism motor subtypes could be detected and which generalize with 89% accuracy in held-out data. The relatively ‘low’ subtype was lower in general intellectual ability and older at age of independent walking, but did not differ in age at first words or autistic traits or symptomatology. Motor noise was considerably higher in the ‘low’ subtype compared to ‘high’ (Cohen’s d = 0.77) or TD children (Cohen’s d = 0.85), but similar between autism ‘high’ and TD children (Cohen’s d = 0.08). Enhanced motor noise in the ‘low’ subtype was also most pronounced during the feedforward phase of reaching actions.LimitationsThe sample size of this work is limited. Future work in larger samples along with independent replication is important. Motor noise was measured only on one specific motor task. Thus, a more comprehensive assessment of motor noise on many other motor tasks is needed.ConclusionsAutism can be split into at least two discrete motor subtypes that are characterized by differing levels of motor noise. This suggests that autism motor subtypes may be underpinned by different biological mechanisms.

Mechanically Induced Motor Tremors Disrupt the Perception of Time.

Contemporary research has begun to show a strong relationship between movements and the perception of time. More specifically, concurrent movements serve to both bias and enhance time estimates. To explain these effects, we recently proposed a mechanism by which movements provide a secondary channel for estimating duration that is combined optimally with sensory estimates. However, a critical test of this framework is that by introducing "noise" into movements, sensory estimates of time should similarly become noisier. To accomplish this, we had human participants move a robotic arm while estimating intervals of time in either auditory or visual modalities (n = 24, ea.). Crucially, we introduced an artificial "tremor" in the arm while subjects were moving, that varied across three levels of amplitude (1-3 N) or frequency (4-12 Hz). The results of both experiments revealed that increasing the frequency of the tremor led to noisier estimates of duration. Further, the effect of noise varied with the base precision of the interval, such that a naturally less precise timing (i.e., visual) was more influenced by the tremor than a naturally more precise modality (i.e., auditory). To explain these findings, we fit the data with a recently developed drift-diffusion model of perceptual decision-making, in which the momentary, within-trial variance was allowed to vary across conditions. Here, we found that the model could recapitulate the observed findings, further supporting the theory that movements influence perception directly. Overall, our findings support the proposed framework, and demonstrate the utility of inducing motor noise via artificial tremors.

Harmonics Traceability and Suppression of Electromagnetic Noise in Fractional Slot Permanent Magnet Synchronous Motors

Harmonics Traceability and Suppression of Electromagnetic Noise in Fractional Slot Permanent Magnet Synchronous Motors

Electric Motor Noise Variation Study Due to Air Gap Effect in Electric Vehicles

Motor whine is a crucial factor in the design of electric motors for electric vehicles (EVs). Predicting noise in a virtual environment is challenging due to the many possible variations during sample testing. The air gap between the stator and rotor in each sample is a significant contributor to radiated noise variation in the electric drive unit (DU). A baseline is first established for radiated noise prediction, assuming a nominal uniform airgap distribution, using the front electric DU in General Motors' Hummer EV. This study explains how the sensitivity of critical motor orders changes with static offset direction when the stiffness of DU is non-uniform and varies with radial direction. It also predicts the range of motor airborne noise variation due to offset orientation. Next, the effect of tilt direction on motor noise variation is studied at different torque conditions and motor speeds. Motor noise is found to be sensitive to tilt direction and angle as the DU stiffness changes axially. Additionally, rotor dynamic offset is investigated, which generates sideband orders in addition to motor pole pass orders. A comparison study is conducted to examine various sideband orders and their central frequency.

Selection of induction motor stator and rotor slot number combination for optimal NVH

With the rise of vehicle electrification, considerable research has been directed towards reducing motor noise, predominantly focusing on Permanent Magnet Synchronous Motors (PMSM). Despite the increasing popularity of the induction motor, driven by its reliability, cost-effectiveness, and lower environmental impact, discussions surrounding the Noise, Vibration, and Harshness (NVH) aspects of induction motors remain limited. This paper addresses the NVH implications associated with stator and rotor slot combinations in conventional squirrel-cage induction motors. Through a design parametric study that examines the impact of varying the number of rotor bars through analytical simulation, the findings not only identify the optimal slot combination for minimizing motor noise but also demonstrate the critical importance of selecting the proper slot configuration, as NVH performance can exhibit significant variations. A physical test was conducted to validate the analytical simulations. This research contributes valuable insights into the induction motor design, especially at the early design stage, emphasizing the necessity of considerations in achieving enhanced NVH performance.

Age-dependent predictors of effective reinforcement motor learning across childhood.

Across development, children must learn motor skills such as eating with a spoon and drawing with a crayon. Reinforcement learning, driven by success and failure, is fundamental to such sensorimotor learning. It typically requires a child to explore movement options along a continuum (grip location on a crayon) and learn from probabilistic rewards (whether the crayon draws or breaks). Here, we studied the development of reinforcement motor learning using online motor tasks to engage children aged 3 to 17 and adults (cross-sectional sample, N=385). Participants moved a cartoon penguin across a scene and were rewarded (animated cartoon clip) based on their final movement position. Learning followed a clear developmental trajectory when participants could choose to move anywhere along a continuum and the reward probability depended on final movement position. Learning was incomplete or absent in 3 to 8-year-olds and gradually improved to adult-like levels by adolescence. A reinforcement learning model fit to each participant identified three age-dependent factors underlying improvement: amount of exploration after a failed movement, learning rate, and level of motor noise. We predicted, and confirmed, that switching to discrete targets and deterministic reward would improve 3 to 8-year-olds' learning to adult-like levels by increasing exploration after failed movements. Overall, we show a robust developmental trajectory of reinforcement motor learning abilities under ecologically relevant conditions i.e., continuous movement options mapped to probabilistic reward. This learning appears to be limited by immature spatial processing and probabilistic reasoning abilities in young children and can be rescued by reducing the demands in these domains.

Dissecting the components of error in analogue report tasks

Over the last two decades, the analogue report task has become a standard method for measuring the fidelity of visual representations across research domains including perception, attention, and memory. Despite its widespread use, there has been no methodical investigation of the different task parameters that might contribute to response variability. To address this gap, we conducted two experiments manipulating components of a typical analogue report test of memory for colour hue. We found that human response errors were independently affected by changes in storage and maintenance requirements of the task, demonstrated by a strong effect of set size even in the absence of a memory delay. In contrast, response variability remained unaffected by physical size of the colour wheel, implying negligible contribution of motor noise to task performance, or by its chroma radius, highlighting non-uniformity of the standard colour space. Comparing analogue report to a matched forced-choice task, we found variation in adjustment criterion made a limited contribution to analogue report variability, becoming meaningful only with low representational noise. Our findings validate the analogue report task as a robust measure of representational fidelity for most purposes, while also quantifying non-representational sources of noise that would limit its reliability in specialized settings.

Reduced precision of motor and perceptual rhythmic timing in autistic adults

Recent results suggest that autistic individuals exhibit reduced accuracy compared to non-autistic peers in temporally coordinating their actions with predictable external cues, e.g., synchronizing finger taps to an auditory metronome. However, it is not yet clear whether these difficulties are driven primarily by motor differences or extend into perceptual rhythmic timing tasks. We recruited autistic and non-autistic participants for an online study testing both finger tapping synchronization and continuation as well as rhythmic time perception (anisochrony detection). We fractionated each participant's synchronization results into parameters representing error correction, motor noise, and internal time-keeper noise, and also investigated error-correcting responses to small metronome timing perturbations. Contrary to previous work, we did not find strong evidence for reduced synchronization error correction. However, we found compelling evidence for noisier internal rhythmic timekeeping in the synchronization, continuation, and perceptual components of the experiment. These results suggest that noisier internal rhythmic timing processes underlie some sensorimotor coordination challenges in autism.

Interference underlies attenuation upon relearning in sensorimotor adaptation.

Savings refers to the gain in performance upon relearning a task. In sensorimotor adaptation, savings is tested by having participants adapt to perturbed feedback and, following a washout block during which the system resets to baseline, presenting the same perturbation again. While savings has been observed with these tasks, we have shown that the contribution from implicit sensorimotor adaptation, a process that uses sensory prediction errors to recalibrate the sensorimotor map, is actually attenuated upon relearning (Avraham et al., 2021). In the present study, we test the hypothesis that this attenuation is due to interference arising from the washout block, and more generally, from experience with a different relationship between the movement and the feedback. In standard adaptation studies, removing the perturbation at the start of the washout block results in a salient error signal in the opposite direction to that observed during learning. As a starting point, we replicated the finding that implicit adaptation is attenuated following a washout period in which the feedback now signals a salient opposite error. When we eliminated visual feedback during washout, implicit adaptation was no longer attenuated upon relearning, consistent with the interference hypothesis. Next, we eliminated the salient error during washout by gradually decreasing the perturbation, creating a scenario in which the perceived errors fell within the range associated with motor noise. Nonetheless, attenuation was still prominent. Inspired by this observation, we tested participants with an extended experience with veridical feedback during an initial baseline phase and found that this was sufficient to cause robust attenuation of implicit adaptation during the first exposure to the perturbation. This effect was context-specific: It did not generalize to movements that were not associated with the interfering feedback. Taken together, these results show that the implicit sensorimotor adaptation system is highly sensitive to memory interference from a recent experience with a discrepant action-outcome contingency.

Investigation of friction and vibration performance of lithium complex grease containing candle soot on aviation electrical machine

The prolonged operation of the motor in the all-electric aircraft can cause the fragmentation and shortening of grease thickener fibers, ultimately resulting in the lubricating grease becoming ineffective. In order to avoid grease failure causing motor winding burnout, this paper uses a four-ball friction testing machine to test the tribological properties of six composite greases containing candle soot with different concentrations, and analyzes the changes in friction coefficient and wear diameter. In addition, by building a test platform for motor vibration and noise, this paper studies the influence of lithium complex grease on vibration and noise characteristics of aviation electrical machine at different propeller speeds. The results show that the addition of 0.04 wt% candle soot lithium grease has the best tribological properties and vibration inhibition properties, because the candle soot in the oil film changes the sliding friction into rolling friction in the contact area of some friction pair. The temperature rise test of aviation electrical machine shows that the lithium complex grease plays an active role in the heat dissipation performance of the high-speed rotating motor.

Noise reduction of axial piston motors using multi-objective optimization of reinforcing ribs based on identification of acoustic sources

The optimization of the housing for reducing vibration and noise in axial piston motors is facing challenges related to inaccurate locations of acoustic sources and inappropriate optimization parameters. In this study, a multi-objective optimization of the thicknesses of the reinforcing ribs for reducing the noise of axial piston motors is investigated by using the compression sensing (CS) method and response surface methodology (RSM). Combined with the CS method, the high-resolution reconstruction of sound-intensity images is used to guide the structural optimization areas through locations of acoustic sources. To reduce vibration and noise, the variable rib structure model (VRSM) is established in structural optimization areas. The thicknesses of reinforcing ribs in different areas are considered optimization variables, while the motor housing's peak vibration acceleration obtained by coupling the motor's dynamic model with the hydraulic model is utilized as the objective function. The mathematical relationship between these variables and the objective function is established through the RSM. Utilizing these functions, a multi-objective optimization model is formulated for discretizing the thicknesses of reinforcing ribs to reduce noise, employing a multi-objective genetic algorithm (MOGA) for optimization calculations. Finally, comparing the sound pressure levels of the axial piston motor with and without the optimized reinforcing ribs, the experimental results demonstrate a notable reduction in noise with the optimized reinforcing ribs. Specifically, there's a reduction of 2.7 dB at the peak frequency of 610 Hz.

A comparasion of the effects of different commutation techniques on acoustic noise in AFPM UAV motors

A comparasion of the effects of different commutation techniques on acoustic noise in AFPM UAV motors

Abnormalities in motor adaptation to different types of perturbations in schizophreniaperturbations in schizophrenia

Schizophrenia is a mental health disorder that often includes psychomotor disturbances, impacting how individuals adjust their motor output based on the cause of motor errors. While previous motor adaptation studies on individuals with schizophrenia have largely focused on large and consistent perturbations induced by abrupt experimental manipulations, such as donning prism goggles, the adaptation process to random perturbations, either caused by intrinsic motor noise or external disturbances, has not been examined – despite its ecological relevance. Here, we used a unified behavioral task paradigm to examine motor adaptation to perturbations of three causal structures among individuals in the remission stage of schizophrenia, youth with ultra-high risk of psychosis, adults with active symptoms, and age-matched controls. Results showed that individuals with schizophrenia had reduced trial-by-trial adaptation and large error variance when adapting to their own motor noise. When adapting to random but salient perturbations, they showed intact adaptation and normal causal inference of errors. This contrasted with reduced adaptation to large yet consistent perturbations, which could reflect difficulties in forming cognitive strategies rather than the often-assumed impairments in procedural learning or sense of agency. Furthermore, the observed adaptation effects were correlated with the severity of positive symptoms across the diagnosis groups. Our findings suggest that individuals with schizophrenia face challenges in accommodating intrinsic perturbations when motor errors are ambiguous but adapt with intact causal attribution when errors are salient.

Research on the characteristics of EV interior sound quality and its dynamic active control system design and development un-der accelerated driving conditions.

In order to improve the interior sound quality of Electric Vehicles (EV), solve the problem of low sense of power and comfort of the interior sound as well as the large electromagnetic excitation order noise of motor and the sharp interior sound, this article designs a dynamic active sound control system for EV under accelerated driving conditions. Firstly, by comparing and analyzing the sound spectrum characteristics of fuel vehicle (FV) and EV during acceleration, a short-time Fourier transform (STFT) is adopted to extract and synthesize the engine sound. Secondly, the influence of the engine order composition and the energy distribution in the frequency domain on the sound quality of the vehicle is analyzed, and an active control system for sound quality is proposed. And the software and hardware development of the active control sound system is completed. Finally, through real-vehicle testing and verification, the sense of comfort and power of the EV interior sound has been greatly improved during acceleration, and the total value of interior sound can meet the requirement. The sound pressure level and loudness of interior sound have been increased, and the sharpness of the sound inside the vehicle has been improved, with a maximum reduction of 1.0acum.