Determination of resonant frequency and quality factor for a sensor system

A method for determining sensor parameters of an actively-driven sensor system may include performing an initialization operation to establish a baseline estimate of the sensor parameters, obtaining as few as three samples of a measured physical quantity versus frequency for the actively-driven sensor system, performing a refinement operation to provide a refined version of the sensor parameters based on the as few as three samples, iteratively repeating the refinement operation until the difference between successive refined versions of the sensor parameters is below a defined threshold, and outputting the refined sensor parameters as updated sensor parameters for the actively-driven sensor system.

FIELD OF DISCLOSURE

The present disclosure relates in general to electronic devices with user interfaces, (e.g., mobile devices, game controllers, instrument panels, etc.), and more particularly, an integrated haptic system for use in a system for mechanical button replacement in a mobile device, for use in haptic feedback for capacitive sensors, and/or other suitable applications.

BACKGROUND

Many traditional mobile devices (e.g., mobile phones, personal digital assistants, video game controllers, etc.) include mechanical buttons to allow for interaction between a user of a mobile device and the mobile device itself. However, such mechanical buttons are susceptible to aging, wear, and tear that may reduce the useful life of a mobile device and/or may require significant repair if malfunction occurs. Also, the presence of mechanical buttons may render it difficult to manufacture mobile devices to be waterproof. Accordingly, mobile device manufacturers are increasingly looking to equip mobile devices with virtual buttons that act as a human-machine interface allowing for interaction between a user of a mobile device and the mobile device itself. Similarly, mobile device manufacturers are increasingly looking to equip mobile devices with other virtual interface areas (e.g., a virtual slider, interface areas of a body of the mobile device other than a touch screen, etc.). Ideally, for best user experience, such virtual interface areas should look and feel to a user as if a mechanical button or other mechanical interface were present instead of a virtual button or virtual interface area.

Presently, linear resonant actuators (LRAs) and other vibrational actuators (e.g., rotational actuators, vibrating motors, etc.) are increasingly being used in mobile devices to generate vibrational feedback in response to user interaction with human-machine interfaces of such devices. Typically, a sensor (traditionally a force or pressure sensor) detects user interaction with the device (e.g., a finger press on a virtual button of the device) and in response thereto, the linear resonant actuator may vibrate to provide feedback to the user. For example, a linear resonant actuator may vibrate in response to user interaction with the human-machine interface to mimic to the user the feel of a mechanical button click.

However, there is a need in the industry for sensors to detect user interaction with a human-machine interface, wherein such sensors provide acceptable levels of sensor sensitivity, power consumption, and size. For example, in an actively driven sensor system, it may be desirable that a signal driver generate a driving signal at or near a resonant frequency of the sensor. Due to manufacturing designs and tolerances as well as environmental effects (such as temperature, humidity, movements in air gap over time) the resonant frequency of the sensor as well as the Q-factor of the sensor may be different for each individual sensor and can change over time. Thus, to ensure generation of driving signal at or near such resonant frequency, it may further be desirable to determine such resonant frequency and/or a quality factor of a sensor.

SUMMARY

In accordance with the teachings of the present disclosure, the disadvantages and problems associated with use of a virtual button in a mobile device may be reduced or eliminated.

In accordance with embodiments of the present disclosure, a method for determining sensor parameters of an actively-driven sensor system may include performing an initialization operation to establish a baseline estimate of the sensor parameters, obtaining as few as three samples of a measured physical quantity versus frequency for the actively-driven sensor system, performing a refinement operation to provide a refined version of the sensor parameters based on the as few as three samples, iteratively repeating the refinement operation until the difference between successive refined versions of the sensor parameters is below a defined threshold, and outputting the refined sensor parameters as updated sensor parameters for the actively-driven sensor system.

In accordance with these and other embodiments of the present disclosure, a system may include an actively-driven sensor and a measurement circuit communicatively coupled to the actively-driven sensor and configured to perform an initialization operation to establish a baseline estimate of sensor parameters of the actively-driven sensor, obtain as few as three samples of a measured physical quantity versus frequency for the actively-driven sensor system, perform a refinement operation to provide a refined version of the sensor parameters based on the as few as three samples, iteratively repeat the refinement operation until the difference between successive refined versions of the sensor parameters is below a defined threshold, and output the refined sensor parameters as updated sensor parameters for the actively-driven sensor system.

Technical advantages of the present disclosure may be readily apparent to one having ordinary skill in the art from the figures, description and claims included herein. The objects and advantages of the embodiments will be realized and achieved at least by the elements, features, and combinations particularly pointed out in the claims.

DETAILED DESCRIPTION

FIG.1illustrates a block diagram of selected components of an example mobile device102, in accordance with embodiments of the present disclosure. As shown inFIG.1, mobile device102may comprise an enclosure101, a controller103, a memory104, a force sensor105, a microphone106, a linear resonant actuator107, a radio transmitter/receiver108, a speaker110, an integrated haptic system112, and a resonant phase sensing system113.

Enclosure101may comprise any suitable housing, casing, or other enclosure for housing the various components of mobile device102. Enclosure101may be constructed from plastic, metal, and/or any other suitable materials. In addition, enclosure101may be adapted (e.g., sized and shaped) such that mobile device102is readily transported on a person of a user of mobile device102. Accordingly, mobile device102may include but is not limited to a smart phone, a tablet computing device, a handheld computing device, a personal digital assistant, a notebook computer, a video game controller, or any other device that may be readily transported on a person of a user of mobile device102.

Controller103may be housed within enclosure101and may include any system, device, or apparatus configured to interpret and/or execute program instructions and/or process data, and may include, without limitation a microprocessor, microcontroller, digital signal processor (DSP), application specific integrated circuit (ASIC), or any other digital or analog circuitry configured to interpret and/or execute program instructions and/or process data. In some embodiments, controller103interprets and/or executes program instructions and/or processes data stored in memory104and/or other computer-readable media accessible to controller103.

Memory104may be housed within enclosure101, may be communicatively coupled to controller103, and may include any system, device, or apparatus configured to retain program instructions and/or data for a period of time (e.g., computer-readable media). Memory104may include random access memory (RAM), electrically erasable programmable read-only memory (EEPROM), a Personal Computer Memory Card International Association (PCMCIA) card, flash memory, magnetic storage, opto-magnetic storage, or any suitable selection and/or array of volatile or non-volatile memory that retains data after power to mobile device102is turned off.

Microphone106may be housed at least partially within enclosure101, may be communicatively coupled to controller103, and may comprise any system, device, or apparatus configured to convert sound incident at microphone106to an electrical signal that may be processed by controller103, wherein such sound is converted to an electrical signal using a diaphragm or membrane having an electrical capacitance that varies as based on sonic vibrations received at the diaphragm or membrane. Microphone106may include an electrostatic microphone, a condenser microphone, an electret microphone, a microelectromechanical systems (MEMs) microphone, or any other suitable capacitive microphone.

Radio transmitter/receiver108may be housed within enclosure101, may be communicatively coupled to controller103, and may include any system, device, or apparatus configured to, with the aid of an antenna, generate and transmit radio-frequency signals as well as receive radio-frequency signals and convert the information carried by such received signals into a form usable by controller103. Radio transmitter/receiver108may be configured to transmit and/or receive various types of radio-frequency signals, including without limitation, cellular communications (e.g., 2G, 3G, 4G, LTE, etc.), short-range wireless communications (e.g., BLUETOOTH), commercial radio signals, television signals, satellite radio signals (e.g., GPS), Wireless Fidelity, etc.

A speaker110may be housed at least partially within enclosure101or may be external to enclosure101, may be communicatively coupled to controller103, and may comprise any system, device, or apparatus configured to produce sound in response to electrical audio signal input. In some embodiments, a speaker may comprise a dynamic loudspeaker, which employs a lightweight diaphragm mechanically coupled to a rigid frame via a flexible suspension that constrains a voice coil to move axially through a cylindrical magnetic gap. When an electrical signal is applied to the voice coil, a magnetic field is created by the electric current in the voice coil, making it a variable electromagnet. The coil and the driver's magnetic system interact, generating a mechanical force that causes the coil (and thus, the attached cone) to move back and forth, thereby reproducing sound under the control of the applied electrical signal coming from the amplifier.

Force sensor105may be housed within enclosure101, and may include any suitable system, device, or apparatus for sensing a force, a pressure, or a touch (e.g., an interaction with a human finger) and generating an electrical or electronic signal in response to such force, pressure, or touch. In some embodiments, such electrical or electronic signal may be a function of a magnitude of the force, pressure, or touch applied to the force sensor. In these and other embodiments, such electronic or electrical signal may comprise a general purpose input/output signal (GPIO) associated with an input signal to which haptic feedback is given. Force sensor105may include, without limitation, a capacitive displacement sensor, an inductive force sensor (e.g., a resistive-inductive-capacitive sensor), a strain gauge, a piezoelectric force sensor, force sensing resistor, piezoelectric force sensor, thin film force sensor, or a quantum tunneling composite-based force sensor. For purposes of clarity and exposition in this disclosure, the term “force” as used herein may refer not only to force, but to physical quantities indicative of force or analogous to force, such as, but not limited to, pressure and touch.

Linear resonant actuator107may be housed within enclosure101, and may include any suitable system, device, or apparatus for producing an oscillating mechanical force across a single axis. For example, in some embodiments, linear resonant actuator107may rely on an alternating current voltage to drive a voice coil pressed against a moving mass connected to a spring. When the voice coil is driven at the resonant frequency of the spring, linear resonant actuator107may vibrate with a perceptible force. Thus, linear resonant actuator107may be useful in haptic applications within a specific frequency range. While, for the purposes of clarity and exposition, this disclosure is described in relation to the use of linear resonant actuator107, it is understood that any other type or types of vibrational actuators (e.g., eccentric rotating mass actuators) may be used in lieu of or in addition to linear resonant actuator107. In addition, it is also understood that actuators arranged to produce an oscillating mechanical force across multiple axes may be used in lieu of or in addition to linear resonant actuator107. As described elsewhere in this disclosure, a linear resonant actuator107, based on a signal received from integrated haptic system112, may render haptic feedback to a user of mobile device102for at least one of mechanical button replacement and capacitive sensor feedback.

Integrated haptic system112may be housed within enclosure101, may be communicatively coupled to force sensor105and linear resonant actuator107, and may include any system, device, or apparatus configured to receive a signal from force sensor105indicative of a force applied to mobile device102(e.g., a force applied by a human finger to a virtual button of mobile device102) and generate an electronic signal for driving linear resonant actuator107in response to the force applied to mobile device102. Detail of an example integrated haptic system in accordance with embodiments of the present disclosure is depicted inFIG.2.

Resonant phase sensing system113may be housed within enclosure101, may be communicatively coupled to force sensor105and linear resonant actuator107, and may include any system, device, or apparatus configured to detect a displacement of a mechanical member (e.g., mechanical member305depicted inFIGS.3A and3B, below) indicative of a physical interaction (e.g., by a user of mobile device102) with the human-machine interface of mobile device102(e.g., a force applied by a human finger to a virtual interface of mobile device102). As described in greater detail below, resonant phase sensing system113may detect displacement of such mechanical member by performing resonant phase sensing of a resistive-inductive-capacitive sensor for which an impedance (e.g., inductance, capacitance, and/or resistance) of the resistive-inductive-capacitive sensor changes in response to displacement of the mechanical member. Thus, displacement of the mechanical member may cause a change in an impedance of a resistive-inductive-capacitive sensor integral to resonant phase sensing system113. Resonant phase sensing system113may also generate an electronic signal to integrated haptic system112to which integrated haptic system112may respond by driving linear resonant actuator107in response to a physical interaction associated with a human-machine interface associated with the mechanical member. Detail of an example resonant phase sensing system113in accordance with embodiments of the present disclosure is depicted in greater detail below.

Although specific example components are depicted above inFIG.1as being integral to mobile device102(e.g., controller103, memory104, force sensor105, microphone106, radio transmitter/receiver108, speakers(s)110), a mobile device102in accordance with this disclosure may comprise one or more components not specifically enumerated above. For example, althoughFIG.1depicts certain user interface components, mobile device102may include one or more other user interface components in addition to those depicted inFIG.1(including but not limited to a keypad, a touch screen, and a display), thus allowing a user to interact with and/or otherwise manipulate mobile device102and its associated components.

FIG.2illustrates a block diagram of selected components of an example integrated haptic system112A, in accordance with embodiments of the present disclosure. In some embodiments, integrated haptic system112A may be used to implement integrated haptic system112ofFIG.1. As shown inFIG.2, integrated haptic system112A may include a digital signal processor (DSP)202, a memory204, and an amplifier206.

DSP202may include any system, device, or apparatus configured to interpret and/or execute program instructions and/or process data. In some embodiments, DSP202may interpret and/or execute program instructions and/or process data stored in memory204and/or other computer-readable media accessible to DSP202.

Memory204may be communicatively coupled to DSP202, and may include any system, device, or apparatus configured to retain program instructions and/or data for a period of time (e.g., computer-readable media). Memory204may include random access memory (RAM), electrically erasable programmable read-only memory (EEPROM), a Personal Computer Memory Card International Association (PCMCIA) card, flash memory, magnetic storage, opto-magnetic storage, or any suitable selection and/or array of volatile or non-volatile memory that retains data after power to mobile device102is turned off.

Amplifier206may be electrically coupled to DSP202and may comprise any suitable electronic system, device, or apparatus configured to increase the power of an input signal VIN(e.g., a time-varying voltage or current) to generate an output signal VOUT. For example, amplifier206may use electric power from a power supply (not explicitly shown) to increase the amplitude of a signal. Amplifier206may include any suitable amplifier class, including without limitation, a Class-D amplifier.

In operation, memory204may store one or more haptic playback waveforms. In some embodiments, each of the one or more haptic playback waveforms may define a haptic response a(t) as a desired acceleration of a linear resonant actuator (e.g., linear resonant actuator107) as a function of time. DSP202may be configured to receive a force signal VSENSEfrom resonant phase sensing system113indicative of force applied to force sensor105. Either in response to receipt of force signal VSENSEindicating a sensed force or independently of such receipt, DSP202may retrieve a haptic playback waveform from memory204and process such haptic playback waveform to determine a processed haptic playback signal VIN. In embodiments in which amplifier206is a Class D amplifier, processed haptic playback signal VINmay comprise a pulse-width modulated signal. In response to receipt of force signal VSENSEindicating a sensed force, DSP202may cause processed haptic playback signal VINto be output to amplifier206, and amplifier206may amplify processed haptic playback signal VINto generate a haptic output signal VOUTfor driving linear resonant actuator107.

In some embodiments, integrated haptic system112A may be formed on a single integrated circuit, thus enabling lower latency than existing approaches to haptic feedback control. By providing integrated haptic system112A as part of a single monolithic integrated circuit, latencies between various interfaces and system components of integrated haptic system112A may be reduced or eliminated.

FIG.3Aillustrates a mechanical member305embodied as a metal plate separated by a distance d from an inductive coil302, in accordance with embodiments of the present disclosure. Mechanical member305may comprise any suitable system, device, or apparatus which all or a portion thereof may displace, wherein such displacement affects an electrical property (e.g., inductance, capacitance, etc.) of the mechanical member305or another electrical component in electrical communication (e.g., via a mutual inductance) with mechanical member305.

FIG.3Billustrates selected components of an inductive sensing system300that may be implemented by force sensor105and/or resonant phase sensing system113, in accordance with embodiments of the present disclosure. As shown inFIG.3, inductive sensing system300may include mechanical member305, modeled as a variable electrical resistance304and a variable electrical inductance306, and may include inductive coil302in physical proximity to mechanical member305such that inductive coil302has a mutual inductance with mechanical member305defined by a variable coupling coefficient k. As shown inFIG.3, inductive coil302may be modeled as a variable electrical inductance308and a variable electrical resistance310.

In operation, as a current I flows through inductive coil302, such current may induce a magnetic field which in turn may induce an eddy current inside mechanical member305. When a force is applied to and/or removed from mechanical member305, which alters distance d between mechanical member305and inductive coil302, the coupling coefficient k, variable electrical resistance304, and/or variable electrical inductance306may also change in response to the change in distance. These changes in the various electrical parameters may, in turn, modify an effective impedance ZLof inductive coil302.

FIG.4illustrates a diagram of selected components of an example system400for performing resonant phase sensing, in accordance with embodiments of the present disclosure. In some embodiments, system400may be used to implement resonant phase sensing system113ofFIG.1. As shown inFIG.4, system400may include a resistive-inductive-capacitive sensor402and a processing integrated circuit (IC)412. In some embodiments, resistive-inductive-capacitive sensor402may implement all or a portion of force sensor105and processing integrated circuit (IC)412may implement all or a portion of resonant phase sensing system113.

As shown inFIG.4, resistive-inductive-capacitive sensor402may include mechanical member305, inductive coil302, a resistor404, and capacitor406, wherein mechanical member305and inductive coil302have a variable coupling coefficient k. Although shown inFIG.4to be arranged in parallel with one another, it is understood that inductive coil302, resistor404, and capacitor406may be arranged in any other suitable manner that allows resistive-inductive-capacitive sensor402to act as a resonant tank. For example, in some embodiments, inductive coil302, resistor404, and capacitor406may be arranged in series with one another. In some embodiments, resistor404may not be implemented with a stand-alone resistor, but may instead be implemented by a parasitic resistance of inductive coil302, a parasitic resistance of capacitor406, and/or any other suitable parasitic resistance.

Processing IC412may be communicatively coupled to resistive-inductive-capacitive sensor402and may comprise any suitable system, device, or apparatus configured to implement a measurement circuit to measure phase information associated with resistive-inductive-capacitive sensor402and based on the phase information, determine a displacement of mechanical member305relative to resistive-inductive-capacitive sensor402. Thus, processing IC412may be configured to determine an occurrence of a physical interaction (e.g., press or release of a virtual button) associated with a human-machine interface associated with mechanical member305based on the phase information.

As shown inFIG.4, processing IC412may include a phase shifter410, a voltage-to-current converter408, a preamplifier440, an intermediate frequency mixer442, a combiner444, a programmable gain amplifier (PGA)414, a voltage-controlled oscillator (VCO)416, a phase shifter418, an amplitude and phase calculation block431, a DSP432, a low-pass filter434, a combiner450, and a frequency and quality factor calculation engine452. Processing IC412may also include a coherent incident/quadrature detector implemented with an incident channel comprising a mixer420, a low-pass filter424, and an analog-to-digital converter (ADC)428, and a quadrature channel comprising a mixer422, a low-pass filter426, and an ADC430such that processing IC412is configured to measure the phase information using the coherent incident/quadrature detector.

Phase shifter410may include any system, device, or apparatus configured to detect an oscillation signal generated by processing IC412(as explained in greater detail below) and phase shift such oscillation signal (e.g., by 45 degrees) such that at a normal operating frequency of system400, an incident component of a sensor signal ϕ generated by preamplifier440is approximately equal to a quadrature component of sensor signal ϕ, so as to provide common mode noise rejection by a phase detector implemented by processing IC412, as described in greater detail below.

Voltage-to-current converter408may receive the phase shifted oscillation signal from phase shifter410, which may be a voltage signal, convert the voltage signal to a corresponding current signal, and drive the current signal on resistive-inductive-capacitive sensor402at a driving frequency with the phase-shifted oscillation signal in order to generate sensor signal ϕ which may be processed by processing IC412, as described in greater detail below. In some embodiments, a driving frequency of the phase-shifted oscillation signal may be selected based on a resonant frequency of resistive-inductive-capacitive sensor402(e.g., may be approximately equal to the resonant frequency of resistive-inductive-capacitive sensor402).

Preamplifier440may receive sensor signal ϕ and condition sensor signal ϕ for frequency mixing, with mixer442, to an intermediate frequency Δf combined by combiner444with an oscillation frequency generated by VCO416, as described in greater detail below, wherein intermediate frequency Δf is significantly less than the oscillation frequency. In some embodiments, preamplifier440, mixer442, and combiner444may not be present, in which case PGA414may receive sensor signal ϕ directly from resistive-inductive-capacitive sensor402. However, when present, preamplifier440, mixer442, and combiner444may allow for mixing sensor signal ϕ down to a lower intermediate frequency Δf which may allow for lower-bandwidth and more efficient ADCs and/or which may allow for minimization of phase and/or gain mismatches in the incident and quadrature paths of the phase detector of processing IC412.

In operation, PGA414may further amplify sensor signal ϕ to condition sensor signal ϕ for processing by the coherent incident/quadrature detector. VCO416may generate an oscillation signal to be used as a basis for the signal driven by voltage-to-current converter408, as well as the oscillation signals used by mixers420and422to extract incident and quadrature components of amplified sensor signal ϕ. As shown inFIG.4, mixer420of the incident channel may use an unshifted version of the oscillation signal generated by VCO416, while mixer422of the quadrature channel may use a 90-degree shifted version of the oscillation signal phase shifted by phase shifter418. As mentioned above, the oscillation frequency of the oscillation signal generated by VCO416may be selected based on a resonant frequency of resistive-inductive-capacitive sensor402(e.g., may be approximately equal to the resonant frequency of resistive-inductive-capacitive sensor402).

In the incident channel, mixer420may extract the incident component of amplified sensor signal ϕ, low-pass filter424may filter out the oscillation signal mixed with the amplified sensor signal ϕ to generate a direct current (DC) incident component, and ADC428may convert such DC incident component into an equivalent incident component digital signal for processing by amplitude and phase calculation block431. Similarly, in the quadrature channel, mixer422may extract the quadrature component of amplified sensor signal ϕ, low-pass filter426may filter out the phase-shifted oscillation signal mixed with the amplified sensor signal ϕ to generate a direct current (DC) quadrature component, and ADC430may convert such DC quadrature component into an equivalent quadrature component digital signal for processing by amplitude and phase calculation block431.

Amplitude and phase calculation block431may include any system, device, or apparatus configured to receive phase information comprising the incident component digital signal and the quadrature component digital signal and based thereon, extract amplitude and phase information.

DSP432may include any system, device, or apparatus configured to interpret and/or execute program instructions and/or process data. In particular, DSP432may receive the phase information and the amplitude information generated by amplitude and phase calculation block431and based thereon, determine a displacement of mechanical member305relative to resistive-inductive-capacitive sensor402, which may be indicative of an occurrence of a physical interaction (e.g., press or release of a virtual button or other interaction with a virtual interface) associated with a human-machine interface associated with mechanical member305based on the phase information. DSP432may also generate an output signal indicative of the displacement. In some embodiments, such output signal may comprise a control signal for controlling mechanical vibration of linear resonant actuator107in response to the displacement.

The phase information generated by amplitude and phase calculation block431may be subtracted from a reference phase ϕrefby combiner450in order to generate an error signal that may be received by low-pass filter434. Low-pass filter434may low-pass filter the error signal, and such filtered error signal may be applied to VCO416to modify the frequency of the oscillation signal generated by VCO416, in order to drive sensor signal ϕ towards reference phase ϕref. As a result, sensor signal ϕ may comprise a transient decaying signal in response to a “press” of a virtual button (or other interaction with a virtual interface) associated with system400as well as another transient decaying signal in response to a subsequent “release” of the virtual button (or other interaction with a virtual interface). Accordingly, low-pass filter434in connection with VCO416may implement a feedback control loop that may track changes in operating parameters of system400by modifying the driving frequency of VCO416.

Frequency and quality factor calculation engine452may comprise any system, device, or apparatus configured to, as described in greater detail below, calculate a resonant frequency f0and/or a quality factor Q associated with resistive-inductive-capacitor sensor402, such as those caused by drift of physical parameters (e.g., aging, temperature, etc.) of force sensor105, mechanical member305, resonant phase sensing system113, etc. AlthoughFIG.4depicts that, in some embodiments, frequency and quality factor calculation engine452is external to DSP432, in some embodiments, functionality of frequency and quality factor calculation engine452may be implemented in whole or part by DSP432.

Although the foregoing contemplates use of closed-loop feedback for sensing of displacement, the various embodiments represented byFIG.4may be modified to implement an open-loop system for sensing of displacement. In such an open-loop system, a processing IC may include no feedback path from amplitude and phase calculation block431to VCO416or variable phase shifter418and thus may also lack a feedback low-pass filter434. Thus, a phase measurement may still be made by comparing a change in phase to a reference phase value, but the oscillation frequency driven by VCO416may not be modified or the phase shifted by variable phase shifter418may not be shifted.

Although the foregoing contemplates use of a coherent incident/quadrature detector as a phase detector for determining phase information associated with resistive-inductive-capacitive sensor402, a resonant phase sensing system112may perform phase detection and/or otherwise determine phase information associated with resistive-inductive-capacitive sensor402in any suitable manner, including, without limitation, using only one of the incident path or quadrature path to determine phase information.

In some embodiments, an incident/quadrature detector as disclosed herein may include one or more frequency translation stages that translate the sensor signal into direct-current signal directly or into an intermediate frequency signal and then into a direct-current signal. Any of such frequency translation stages may be implemented either digitally after an analog-to-digital converter stage or in analog before an analog-to-digital converter stage.

In addition, although the foregoing contemplates measuring changes in resistance and inductance in resistive-inductive-capacitive sensor402caused by displacement of mechanical member305, other embodiments may operate based on a principle that any change in impedance based on displacement of mechanical member305may be used to sense displacement. For example, in some embodiments, displacement of mechanical member305may cause a change in a capacitance of resistive-inductive-capacitive sensor402, such as if mechanical member305included a metal plate implementing one of the capacitive plates of capacitor406.

Although DSP432may be capable of processing phase information to make a binary determination of whether physical interaction associated with a human-machine interface associated with mechanical member305has occurred and/or ceased to occur, in some embodiments, DSP432may quantify a duration of a displacement of mechanical member305to more than one detection threshold, for example to detect different types of physical interactions (e.g., a short press of a virtual button versus a long press of the virtual button). In these and other embodiments, DSP432may quantify a magnitude of the displacement to more than one detection threshold, for example to detect different types of physical interactions (e.g., a light press of a virtual button versus a quick and hard press of the virtual button).

AlthoughFIG.4and the description thereof depicts particular embodiments of a resonant phase sensing system, other architectures for force sensing may be used consistent with this disclosure, including without limitation the various resonant phase sensing system architectures described in U.S. patent application Ser. No. 16/267,079, filed Feb. 4, 2019. Thus, while frequency and quality factor calculation engine452is discussed herein in relation to operation in connection with a resonant phase sensing system, frequency and quality factor calculation engine452may be used with any other suitable force sensing system.

Accordingly, using the systems and methods described above, a resistive-inductor-capacitive sensor is provided wherein part of the inductive component is exposed to the user in the form of a metal plate of a region of a chassis or enclosure (e.g., enclosure101). As such, displacements in the metal plate or enclosure may correlate to changes in measured phase or amplitude.

As mentioned in the Background section of this application, for an actively-driven sensor system, it may be desirable that a signal driver (e.g., voltage-to-current converter408) generate a signal at the resonant frequency of the sensor. Due to manufacturing designs and tolerances as well as environmental effects (e.g., temperature, humidity, movements in air gap over time, other changes in mechanical structures, etc.), resonant frequency f0and/or quality factor Q of resistive-inductive-capacitive sensor402may be different from each individual sensor and may change over time. There are many reasons to operate resistive-inductive-capacitive sensor402at or near resonant frequency f0, including without limitation:As system400is a phase measurement system, the phase slope of the sensor may be approximately linear and may have its highest sensitivity close to resonant frequency f0. Accordingly, operating with a carrier frequency of the driving signal at or near resonant frequency f0may optimize performance of system400.At frequencies away from resonant frequency f0, a signal amplitude developed across resistive-inductive-capacitive sensor402may be reduced, due to a smaller impedance presented by resistive-inductive-capacitive sensor402. This smaller signal amplitude may lead to a decrease in a signal-to-noise-ratio (SNR) of system400.Quality factor Q of resistive-inductive-capacitive sensor402may play a major role in translating the measured sensor signal ϕ into force. Measuring a changing quality factor Q over time may allow for system400to compensate for changes in a phase-to-force translation. (Compensation for changing quality factor Q is outside the scope of this disclosure).

Accordingly, as described in detail below, frequency and quality factor calculation engine452may be configured to determine resonant frequency f0and quality factor Q of resistive-inductive-capacitive sensor402, and to adjust the drive frequency of a driving signal for resistive-inductive-capacitive sensor402(e.g., driven by voltage-to-current converter408accordingly). As a result, system400may measure relevant parameters, estimate changed values of the sensor parameters, and make some internal adjustments to “re-center” VCO416and drive circuitry of system400to the optimal values for resistive-inductive-capacitive sensor402.

In some embodiments, frequency and quality factor calculation engine452may employ a heuristic approach to determine resonant frequency f0and quality factor Q of resistive-inductive-capacitive sensor402.FIG.5illustrates an example graph of amplitude versus frequency for resistive-inductive-capacitive sensor402. As shown inFIG.5, if resonant frequency f0and quality factor Q are known, measurements of amplitude taken at an equally defined delta frequency Δf both less than and greater than resonant frequency f0may result in an equal measurement (or approximately equal measurement within reasonable measurement tolerances) of amplitude. In other words, a measured amplitude at f0−Δf should equal a measured amplitude at f0+Δf. However, if an estimated resonant frequency festis not equal to the actual resonant frequency f0, a difference may exist in measured amplitudes at fest—Δf and at f0+Δf. Thus if fest<f0, it is expected that the amplitude at fest−Δf will be less than the amplitude at f0+Δf, as shown inFIG.6.

Frequency and quality factor calculation engine452may be configured to, based on these observations, correct estimated resonant frequency festbased on differences of amplitudes and correct quality factor Q based on average amplitudes.

FIG.7illustrates a flow chart of an example method700for a heuristic approach for determining resonant frequency f0and quality factor Q for resistive-inductive-capacitive sensor402, in accordance with certain embodiments of the present disclosure. According to one embodiment, method700may begin at step702. As noted above, teachings of the present disclosure may be implemented in a variety of configurations of system400. As such, the preferred initialization point for method700and the order of the steps comprising method700may depend on the implementation chosen.

At step702, frequency and quality factor calculation engine452may obtain three sample measurements of amplitude versus frequency for resistive-inductive-capacitive sensor402: (a) one at an estimated resonant frequency festminus a delta frequency Δf, wherein delta frequency Δf equals the estimated resonant frequency festdivided by two times quality factor Q (Δf=fest/2Q); (b) one at the estimated resonant frequency fest; and (c) one at the estimated resonant frequency festplus the delta frequency Δf.

At step704, frequency and quality factor calculation engine452may perform detection of a peak amplitude from the three sample measurements. For example, if the amplitude measurement at either of fest−Δf or fest+Δf yields a greater amplitude than the amplitude measurement at fest, then frequency and quality factor calculation engine452may determine that a peak has not been found. At step706, if the peak has been found, method700may proceed to step710. Otherwise, method700may proceed to step708.

At step708, as a result of no peak being found, frequency and quality factor calculation engine452may update estimated resonant frequency fest. For example, if the amplitude measurement at fest−Δf yielded a greater amplitude than the amplitude measurement at fest, then frequency and quality factor calculation engine452may decrease estimated resonant frequency festby a predetermined amount. As another example, if the amplitude measurement at fest+Δf yielded a greater amplitude than the amplitude measurement at fest, then frequency and quality factor calculation engine452may increase estimated resonant frequency festby a predetermined amount.

After completion of step708, method700may proceed to step722which (as explained below) may result in steps702through708repeating until frequency and quality factor calculation engine452finds the peak as described above.

At step710, as a result of the peak being found, frequency and quality factor calculation engine452may proceed to a second phase of operation of the heuristic approach in which quality factor Q and estimated resonant frequency festmay be refined, as discussed below in reference toFIG.8. As shown inFIG.8, frequency and quality factor calculation engine452may determine amplitude values A0, A1a, A1b, A1, A2, A2a and A2b at the various probe frequencies. The probe frequencies are determined as follows based on the most recent estimates of quality factor Q and estimated resonant frequency fest:

f2=fest(for which amplitude A0 is determined); and

The second phase of operation of the heuristic approach may begin at step710wherein frequency and quality factor calculation engine452may update quality factor Q. For example, frequency and quality factor calculation engine452may update quality factor Q in accordance with:

Qnew=Qprevious[1-Qslp(magnorm-22)]
where Qnewis a newly-calculated value for quality factor Q, Qpreviousis the previous value for quality factor Q, Qslpis a Q factor learn rate, a magnormis a normalized magnitude given by:

A speed of convergence to correct quality factor Q may depend on Q factor learn rate Qslp. Q factor learn rate Qslpmay be set to a fixed value or frequency and quality factor calculation engine452may adapt Q factor learn rate Qslpon-the-fly to ensure fastest convergence. For example, a Q factor learn rate estimator may be implemented by frequency and quality factor calculation engine452to calculate Q factor learn rate Qslpas follows:

Qslp=1-QactQpreviosmagnorm-22
where Qactis the actual quality factor of resistive-inductive-capacitive sensor402.

For example, with reference toFIGS.9A,9B, and9C, the value of Q factor learn rate Qslpis plotted for three different values of actual quality factor Qaet(e.g., 5, 10, and 15), with previous quality factor estimate Qpreviousswept from 5 to 15 in steps of 0.1. From these figures, it can be seen that:If Qest>Qact(indicated by magnorm>√2/2), then Qslp≈2.4;If Qest<Qact(indicated by magnorm<√2/2), then Qslp≈3.5; andIf Qest≈Qact(indicated by magnorm≈√2/2), then Qslp≈0.

Accordingly, frequency and quality factor calculation engine452may use the foregoing scheme to determine an optimum value for Q factor learn rate Qslp. Selecting a value for Q factor learn rate Qslpsmaller than an optimum value may lead to an over-damped response while selecting a value for Q factor learn rate Qslp.

At step712, frequency and quality factor calculation engine452may determine whether the newly-calculated value Qnewfor quality factor Q is within a predetermined range. If the newly-calculated value Qnewis outside the pre-determined range, method700may proceed to step714. Otherwise, method700may proceed to step716.

At step714, in response to the newly-calculated value Qnewfor quality factor Q being outside the predetermined range, which may denote an error condition, frequency and quality factor calculation engine452may flag the error. After completion of step714, method700may end.

At step716, frequency and quality factor calculation engine452may update estimated resonant frequency fest. For example, frequency and quality factor calculation engine452may update estimated resonant frequency festin accordance with:

fest=fprevious[1+fslp(A⁢2-A⁢1A⁢0)]
where festis the newly-calculated value for estimated resonant frequency fest, fpreviousis the previous value for estimated resonant frequency fest, and fslpis a frequency learn rate.

A speed of convergence to correct estimated resonant frequency festmay depend on frequency learn rate fslpFrequency learn rate fslpmay be set to a fixed value or frequency and quality factor calculation engine452may adapt frequency learn rate fslpon-the-fly to ensure fastest convergence. For example, a frequency learn rate estimator may be implemented by frequency and quality factor calculation engine452to calculate frequency learn rate fslpas follows:

fslp=f0fprevios-1A⁢2-A⁢1A⁢0
where f0is the actual resonant frequency of resistive-inductive-capacitive sensor402.

For example, with reference toFIG.10, the value of frequency learn rate fslpis plotted for three different values of actual quality factor Qact(e.g., 5, 10, and 15) for an example resistive-inductive-capacitive sensor402having a resonant frequency f0of 20 MHz.

FromFIG.10, it may be seen that as estimated resonant frequency festdiverges from resonant frequency f0, frequency learn rate fslpapproaches √{square root over (2)}/2Q. Accordingly, frequency learn rate fslpis dependent upon actual quality factor Qact, and the optimal frequency learn rate fslpmay increase as estimated resonant frequency festapproaches resonant frequency f0.

As mentioned previously, in some embodiments, frequency learn rate fslpmay be fixed. A negative-sloping frequency learn rate fslpat frequencies above resonant frequency f0. may be seen because amplitude magnitude may not be perfectly symmetric about resonant frequency f0due to a presence of a transfer function zero formed by inductance and series resistance of resistive-inductive-capacitive sensor402.

At step718, frequency and quality factor calculation engine452may determine whether the newly-calculated value of estimated resonant frequency festis within a predetermined range. If the newly-calculated of estimated resonant frequency festis outside the pre-determined range, method700may proceed to step720. Otherwise, method700may proceed to step722.

At step720, in response to the newly-calculated estimated resonant frequency festbeing outside the predetermined range, which may denote an error condition, frequency and quality factor calculation engine452may flag the error. After completion of step720, method700may end.

At step722, frequency and quality factor calculation engine452may perform a “check iteration” step wherein a change in each of estimated resonant frequency festand quality factor Q occurring during the then-present iteration through the loop of method700is below respective thresholds. In addition, frequency and quality factor calculation engine452may determine if the number of iterations of the loop of method700has exceeded a maximum iteration count to prevent the loop from executing without bound. At step724, frequency and quality factor calculation engine452may determine whether the results of the comparisons of the check iteration step warrant executing the loop of method700again. If the results of the comparisons of the check iteration step warrant executing the loop of method700again, method700may proceed again to step702. Otherwise, method700may end.

AlthoughFIG.7discloses a particular number of steps to be taken with respect to method700, method700may be executed with greater or fewer steps than those depicted inFIG.7. In addition, althoughFIG.7discloses a certain order of steps to be taken with respect to method700, the steps comprising method700may be completed in any suitable order.

Method700may be implemented using system400or any other system operable to implement method700. In certain embodiments, method700may be implemented partially or fully in software and/or firmware embodied in computer-readable media.

In certain embodiments, variations to the heuristics approach described above may be employed. For example, in some embodiments, more than three measurement points (e.g., A1a, A1b, A2a, and A2b in addition to A0, A1, and A2) may be used for either of the peak detection or parameter update phases of method700in order to provide more accurate estimates. Further, in these and other embodiments, the measurement points may not be equally spaced or symmetric around the estimated resonant frequency.

In addition, in these and other embodiments, the frequency values chosen may be dynamic instead of static. For example, in some embodiments, amplitude and phase values of a previous iteration may be used to determine the new frequency measurement values (e.g., the frequency values themselves and/or the number of frequency measurement values). As a specific example, if a previous iteration showed amplitude values indicating the system was significantly above the resonance value (e.g., monotonically decreasing amplitude with increasing frequency), frequency and quality factor calculation engine452may choose the frequency values for the subsequent iteration to be frequencies less than that of the previous iteration.

In these and other embodiments, frequency and quality factor calculation engine452may use phase information in lieu of or in addition to amplitude information in order to achieve faster convergence.

In these and other embodiments, frequency and quality factor calculation engine452may perform the peak detection/update phase and/or the parameter update phase in a reduced number of iterations by using a more sophisticated function of the amplitude values, phase values, or both at the various frequency values.

In these and other embodiments, frequency and quality factor calculation engine452may use a binary search during peak detection.

In some embodiments, frequency and quality factor calculation engine452may employ a system identification and curve fit approach to determine resonant frequency f0and quality factor Q of resistive-inductive-capacitive sensor402. To illustrate, system400may have a specific transfer function. In many cases, resistive-inductive-capacitive sensor402is likely to be the main contributor to that transfer function. If the transfer function is known, frequency and quality factor calculation engine452may obtain data samples and use them to estimate the sensor parameters of interest such as quality factor Q and resonant frequency f0. Frequency and quality factor calculation engine452may use different characteristics of the transfer function (e.g., amplitude, phase, quadrature components, etc.) to perform such estimation.

The system identification and curve fit approach may be outlined as follows. Frequency and quality factor calculation engine452may determine sensor output amplitude and/or phase for at least three distinct driving frequencies. While as few as three driving frequencies may be used, more drive frequencies may be used. Frequency and quality factor calculation engine452may further fit a transfer function to the measured magnitude and/or phase. For example, a transfer function Z(s) of an ideal resistive-inductive-capacitive network may take the form of:

Frequency and quality factor calculation engine452may use any suitable curve fit or parameters estimation method, including without limitation the Nelder-Mead method, Broyden's Method, or the Levenberg-Marquardt algorithm. Frequency and quality factor calculation engine452may determine a “goodness of the fit” by an error function which may be either minimized or maximized by the above-described curve fit method. Examples of an error function may include, without limitation, sum of least square error and sum of absolute value of error.

FIG.11illustrates a flow chart of an example method1100for a system identification and curve fit approach for determining resonant frequency f0and quality factor Q for resistive-inductive-capacitive sensor402, in accordance with certain embodiments of the present disclosure. According to one embodiment, method1100may begin at step1102. As noted above, teachings of the present disclosure may be implemented in a variety of configurations of system400. As such, the preferred initialization point for method1100and the order of the steps comprising method1100may depend on the implementation chosen.

At step1102, frequency and quality factor calculation engine452may initially estimate sensor parameters (e.g., estimated quality factor Qestand estimated resonant frequency fest) to provide a baseline to begin the system identification and curve fit approach.

At step1104, frequency and quality factor calculation engine452may obtain a fixed number (e.g., as few as three) of samples of the transfer function curve (e.g., amplitude and/or phase versus frequency) for system400. Preferably, the samples obtained may be at or near resonant frequency f0. In addition or alternatively, preferably a number of samples obtained should be at least one more than the order of the equation being fit (e.g., three or more samples for a second-order transfer function). In addition, preferably a number of samples obtained should be at least one more than the number of sensor parameters (e.g., three or more samples for two sensor parameters of quality factor Q and estimated resonant frequency fest).FIG.12illustrates example graphs of amplitude versus frequency and phase versus frequency for a resistive-inductive-capacitive sensor depicting example sample points that may be acquired by frequency and quality factor calculation engine452in this step1104, in accordance with embodiments of the present disclosure.

In order to ensure that the sample points have been selected appropriately, frequency and quality factor calculation engine452may check one or more conditions before proceeding with a sensor parameter estimation. For example, for a three-point curve fit:preferably, the phase across the three sample points may not increase as the frequency increases;preferably, of the three points, the middle point may be the amplitude inflection point;preferably, the amplitude of the third point may be greater than the amplitude of the first point;preferably, the difference between the phase of the first two points may be lesser than or equal to the difference in the phase of the last two points; andpreferably, the phase of at least two of the points may be lesser than the quiescent phase (i.e., the operating phase of the sensor).

Thus, the selected sample points may be initially probed or sampled, and the selected points are validated to ensure that suitable points have been selected. If not, frequency and quality factor calculation engine452may update the sample points. In a preferred implementation, frequency and quality factor calculation engine452may be operable to repeat the sampling operation for a number of iterations or for values within a threshold limit, above which the method is halted and an interrupt generated for an associated system or controller, for example to generate a device error or prompt a more general device reset or recalibration.

At step1106, frequency and quality factor calculation engine452may process the samples obtained using a chosen curve fit method using the estimated sensor parameters (estimated quality factor Qestand estimated resonant frequency fest) in order to calculate sensor outputs. At step1108, frequency and quality factor calculation engine452may compare calculated sensor outputs with measured results using an error function, as described above.

At step1110, frequency and quality factor calculation engine452may determine if the error function is within a predetermined tolerance. If the frequency and quality factor calculation engine452determines that the error function is within the predetermined tolerance, method1100may end, and the most-recently updated sensor parameters (e.g., estimated quality factor Qestand estimated resonant frequency fest) may be established as the final estimates of the sensor parameters. On the other hand, if frequency and quality factor calculation engine452determines that the error function is not within the predetermined tolerance, method1100may proceed again to step1112.

At step1112, frequency and quality factor calculation engine452may update the estimated sensor parameters (e.g., estimated quality factor Qestand estimated resonant frequency fest) in an attempt to reduce the error function on the next iteration of steps1106-1110. After completion of step1112, method1100may proceed again to step1106.

AlthoughFIG.11discloses a particular number of steps to be taken with respect to method1100, method1100may be executed with greater or fewer steps than those depicted inFIG.11. In addition, althoughFIG.11discloses a certain order of steps to be taken with respect to method1100, the steps comprising method1100may be completed in any suitable order.

Method1100may be implemented using system400or any other system operable to implement method1100. In certain embodiments, method1100may be implemented partially or fully in software and/or firmware embodied in computer-readable media.

In at least one aspect, the presence of parasitics may create secondary resonance points in system400. To prevent inaccurate results, additional checks may be performed. For example, the amplitude of the signal at the estimated resonance frequency f0may be measured and compared with the sensor impedance. If the amplitude is too low, e.g., below a defined threshold, this could be as a result of a secondary resonance within the system (or a higher than desired error in the final result).

Additionally or alternatively, the phase of the measured signal at the estimated resonance frequency f0may be compared with the sensor phase at resonance. If the measured signal phase at resonance is too low, e.g., below a defined threshold, this could be as a result of a secondary resonance within the system (or a higher than desired error in the final result).

In at least a further aspect, the measured amplitude and phase from the phase detector may be used to validate the accuracy of the estimated quality factor Q and/or resonance frequency f0. In such systems, the algorithm may be re-run with different frequency sample points and/or additional sample points.

Accordingly, there is described a sensor system having a system for updating a quality factor Q and resonant frequency f0of a sensor system (e.g., sensor system400), to accommodate for changes in sensor performance due to time, changes in ambient or environmental conditions, and/or due to external interference.

It will be understood that the above-described methods may be implemented in a suitable controller or processor as shown in the above figures. The controller may be provided as an integral part of the sensor system, for example processing IC412ofFIG.4, or may be provided as part of a centralized controller such as a central processing unit (CPU) or applications processor (AP). It will be understood that the controller may be provided with a suitable memory storage module for storing data for use in the above-described methods.

It will further be understood that the above-describe methods may be implemented as part of a trained machine-learning module, for example a machine-learning module trained to estimate updated values for quality factor Q and/or resonance frequency f0based on monitored data points or probe points, as described above.

It should be apparent to those skilled in the art that while this is being taught in terms of a particular inductive sensor system, any sensor system in which a quality factor Q and/or a resonant frequency f0of the sensor system may require correction may benefit from the methods and systems taught herein.