Adaptive Filter for Mechanical Impedance Identification in Electromagnetic Loads
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Solution Overview
Problem
Existing methods for determining the mechanical impedance of electromagnetic loads, such as linear resonant actuators, are sensitive to noise and suffer from slow convergence, leading to inefficiencies in driving haptic transducers and adapting playback signals to changing load parameters.
Innovation Solution
A system that generates a waveform signal to drive the electromagnetic load and uses adaptive filter circuitry to identify mechanical impedance parameters by processing current and back electromotive force signals, with coefficient adaptation based on derived signals from these measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods are used to determine mechanical impedance of electromagnetic loads, then the impedance parameters can be identified, but the system is sensitive to noise and suffers from slow convergence
Solution Approach 1:
The patent introduces an adaptive filter as an intermediary component between the electromagnetic load and the impedance determination system. This filter processes the electrical signals (current and voltage) to extract accurate mechanical impedance parameters while rejecting noise. The adaptive filter acts as a mediator that separates the useful signal containing impedance information from the noisy measurements, thereby improving measurement precision without compromising reliability.
Solution Approach 2:
The patent implements a feedback mechanism where the adaptive filter continuously adjusts its parameters based on the measured electrical signals from the electromagnetic load. The system monitors the current and voltage signals, processes them through the adaptive filter, and uses the resulting impedance parameter estimates to optimize filter performance. This closed-loop feedback approach enables the system to converge quickly to accurate impedance values while maintaining robustness against noise through continuous adaptation.
2Measurement precision
If traditional methods are used to determine mechanical impedance of electromagnetic loads, then the impedance parameters can be identified, but the convergence speed is slow
Solution Approach 1:
The patent employs a dynamic adaptive filter that continuously adjusts its characteristics based on the input signals from the electromagnetic load. Rather than using fixed filter parameters, the system dynamically modifies the filter's transfer function to optimize the extraction of mechanical impedance parameters. This dynamic adaptation enables the system to converge quickly to accurate impedance values even in the presence of varying operating conditions, resolving the contradiction between measurement precision and convergence speed.
3Productivity
If haptic transducers are operated at resonance frequency for efficient tonal vibration, then notification efficiency is improved, but the resonance frequency varies over time due to sample-to-sample variations, assembly variations, aging, and use conditions
Solution Approach 1:
The patent uses feedback from the adaptive filter to continuously track the resonance frequency of the haptic transducer. By monitoring the electrical signals and processing them through the adaptive filter, the system identifies changes in resonance frequency caused by sample-to-sample variations, assembly differences, aging, or usage conditions. This feedback mechanism enables real-time adjustment of the driving frequency to maintain operation at the current resonance peak, thereby preserving notification efficiency despite drift in the transducer's resonant characteristics.
Solution Approach 2:
The system dynamically adapts to changing resonance frequency by continuously updating the driving frequency based on impedance parameter identification. The adaptive filter enables the system to track resonance frequency variations over time and adjust the excitation frequency accordingly. This dynamic operation ensures that the haptic transducer remains operated at its current resonance frequency, maintaining efficient tonal vibration generation for notifications even as the transducer's characteristics change due to aging, assembly variations, or usage conditions.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces noise sensitivity and enables efficient identification of mechanical impedance parameters, allowing for optimized signal playback and adaptation to changing load conditions, thereby improving haptic feedback in devices.
Implementation Method 1
Vibro-haptic transducers, for example linear resonant actuators (LRAs), are widely used in portable devices such as mobile phones to generate vibrational feedback to a user
Implementation Method 2
receive a current signal representative of a current associated with the electromagnetic load and a back electromotive force signal representative of a back electromotive force associated with the electromagnetic load
Data Source
AI summary
A method for identifying a mechanical impedance of an electromagnetic load may include generating a waveform signal for driving an electromagnetic load and, during driving of the electromagnetic load by the waveform signal or a signal derived therefrom, receiving a current signal representative of a current associated with the electromagnetic load and a back electromotive force signal representative of a back electromotive force associated with the electromagnetic load. The method may also include implementing an adaptive filter to identify parameters of the mechanical impedance of the electromagnetic load, wherein an input of a coefficient control for adapting coefficients of the adaptive filter is a first signal derived from the back electromotive force signal and a target of the coefficient control for adapting coefficients of the adaptive filter is a second signal derived from the current signal.