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Adaptive Time-Domain Harmonic Control for Noise-Vibration-Harshness Reduction of Electric Drives

Klaus Herburger, Fabian Jakob, David Gänzle, Maximilian Manderla, Andrea Iannelli

TL;DR

The paper tackles NVH reduction in electric drives by introducing an adaptive time-domain harmonic controller embedded in the drive’s control loop. It proposes three integration structures, a computationally efficient online parameter estimator, and a delta-learning scheme with a lookup-table feedforward to maintain robustness across operating points. Validation through simulations and a hardware testbench demonstrates faster convergence and significant NVH reductions, even during speed changes and for multiple harmonics. The work delivers a practical, stability-grounded approach for real-time NVH mitigation in electric drives with potential longevity and user-comfort benefits.

Abstract

Reducing Noise, Vibration, and Harshness (NVH) in electric drives is crucial for applications such as electric vehicle drivetrains and heat-pump compressors, where strict NVH requirements directly affect user satisfaction and component longevity. This work presents the integration of an adaptive time-domain harmonic controller into an existing electric-drive control loop to attenuate harmonic disturbances. Three control structures are proposed and analyzed, along with a modified parameter-estimation scheme that reduces computational effort while preserving estimation accuracy, making the method suitable for embedded real-time implementation. To cope with fast operating-point changes, a delta-learning approach combines adaptive control with a lookup-table-based feedforward estimator, ensuring fast convergence and robustness. The proposed controller architectures are validated through simulation and testbench experiments on a permanent-magnet synchronous machine drive, demonstrating substantial NVH reductions across operating conditions. The results confirm that time-domain adaptive harmonic control offers a practical and theoretically grounded solution for real-time NVH mitigation in electric drives.

Adaptive Time-Domain Harmonic Control for Noise-Vibration-Harshness Reduction of Electric Drives

TL;DR

The paper tackles NVH reduction in electric drives by introducing an adaptive time-domain harmonic controller embedded in the drive’s control loop. It proposes three integration structures, a computationally efficient online parameter estimator, and a delta-learning scheme with a lookup-table feedforward to maintain robustness across operating points. Validation through simulations and a hardware testbench demonstrates faster convergence and significant NVH reductions, even during speed changes and for multiple harmonics. The work delivers a practical, stability-grounded approach for real-time NVH mitigation in electric drives with potential longevity and user-comfort benefits.

Abstract

Reducing Noise, Vibration, and Harshness (NVH) in electric drives is crucial for applications such as electric vehicle drivetrains and heat-pump compressors, where strict NVH requirements directly affect user satisfaction and component longevity. This work presents the integration of an adaptive time-domain harmonic controller into an existing electric-drive control loop to attenuate harmonic disturbances. Three control structures are proposed and analyzed, along with a modified parameter-estimation scheme that reduces computational effort while preserving estimation accuracy, making the method suitable for embedded real-time implementation. To cope with fast operating-point changes, a delta-learning approach combines adaptive control with a lookup-table-based feedforward estimator, ensuring fast convergence and robustness. The proposed controller architectures are validated through simulation and testbench experiments on a permanent-magnet synchronous machine drive, demonstrating substantial NVH reductions across operating conditions. The results confirm that time-domain adaptive harmonic control offers a practical and theoretically grounded solution for real-time NVH mitigation in electric drives.

Paper Structure

This paper contains 33 sections, 2 theorems, 56 equations, 15 figures, 3 tables.

Key Result

Theorem 1

Consider the closed-loop system closedloop that is generated using the estimation eq:al and the control eq:control and consider the parameter estimation error eq:estierror. Assume that Assumption assum:standing is satisfied. Then, for all $\alpha > \frac{\gamma_\mathrm{G}}{2} + q \gamma_\mathrm{p}$,

Figures (15)

  • Figure 1: Control loop without HC.
  • Figure 2: Control architectures considered in this work. The shaded area indicates the part of the system assumed unknown. (a) Structure 1 -- Acceleration to voltage. (b) Structure 2 -- Acceleration to measured current. (c) Structure 3 -- Acceleration to reference current.
  • Figure 3: Feedback interconnection with adaptive time-domain harmonic controller (inside shaded area).
  • Figure 4: Delta learning adaptive controller.
  • Figure 5: Adaptive delta learning structure.
  • ...and 10 more figures

Theorems & Definitions (3)

  • Theorem 1
  • Proposition 1
  • proof