Keyed force adjustment feedback system

Abstract

The application relates to the technical field of force feedback, and discloses an adjustable force feedback system of a keyboard key, which comprises an inductance shaft assembly, a sensor module, a feedback force adjusting module, a control processing module, a user configuration interface and an output device, the feedback force adjusting module is used for generating a combined feedback force of electromagnetic force and mechanical force, the combined feedback force comprises electromagnetic force determined by coil current and key displacement and mechanical force determined by an elastic element and a damping element. Through the synergistic effect technology of electromagnetic feedback force and mechanical feedback force, the real-time data input of an optimization algorithm and the sensor module are combined, precise dynamic adjustment and energy consumption optimization of the key feedback force are realized, and multiple paragraph feeling feedback is provided through PWM signals and nonlinear elastic design. The prediction control algorithm is used to improve the feedback speed and continuity, so that the defects of single key stroke feedback mode, slow adjustment speed and insufficient use scene adaptability are solved, and various operation requirements are met.

Description

Technical Field

[0001] This invention relates to the field of force feedback technology, specifically to an adjustable force feedback system for keyboard keys. Background Technology

[0002] With the widespread use of keyboards in gaming, office work, and professional design, users have placed higher demands on key feedback performance. However, existing keyboard technology still has many shortcomings in terms of flexible adjustment of feedback force and personalized experience.

[0003] Traditional mechanical keyboards primarily use springs and physical contacts for feedback. While offering a clear tactile feedback, the reliance on a fixed mechanical design makes dynamic adjustment difficult. Users cannot adjust the key tactile feedback or rebound speed according to their needs, resulting in poor adaptability to various usage scenarios. For example, office environments require gentle key feedback, while gaming demands stronger feedback and a more tactile feel—diverse needs that mechanical keyboards cannot meet.

[0004] Optical axis keyboards use optical sensing technology to replace traditional mechanical contacts. While this improves key durability and sensitivity, the feedback force remains somewhat limited. The feedback characteristics of optical axes largely rely on a fixed mechanical structure, making it impossible to precisely adjust according to the depth or speed of the user's press. During high-frequency operation, the lack of variation in key feedback fails to meet users' high standards for sensitivity and operational comfort.

[0005] Magnetic switch keyboards use electromagnetic force to provide key feedback. While this improves non-contact responsiveness to some extent, the feedback force is often fixed, lacking the flexibility for dynamic adjustment. Many magnetic switch keyboards exhibit response delays in real-time feedback force adjustment, resulting in users not receiving timely and accurate feedback during rapid keystrokes. Furthermore, electromagnetic feedback designs suffer from high power consumption; the heat buildup in the electromagnetic coils during frequent use can negatively impact keyboard performance and lifespan.

[0006] Current keyboard technology typically employs a uniform feedback design, making it difficult to support independent adjustment of key areas. Whether mechanical, optical, or magnetic keyboards, the feedback characteristics of all keys are generally consistent, neglecting the need for regionalized key operations. In games, users prefer stronger tactile feedback for key presses, while other areas require lighter feedback. Current technology still lacks effective means to achieve regionalized and personalized adjustments. Summary of the Invention

[0007] To address the shortcomings of existing technologies, this invention provides an adjustable key feedback system for keyboards, which solves the problem that existing keyboard key feedback force cannot be dynamically adjusted in real time according to user needs, and is difficult to meet personalized feedback needs in multiple scenarios.

[0008] To achieve the above objectives, the present invention provides the following technical solution: an adjustable force feedback system for keyboard keys, comprising,

[0009] The inductive shaft assembly is used to sense the pressed state of the button and generate feedback force by acting on the button shaft through electromagnetic force;

[0010] The sensor module is used to collect information on the pressure applied to the button, the speed of the press, and the displacement of the press.

[0011] The feedback force adjustment module is used to coordinate the adjustment of electromagnetic force and mechanical force according to the target feedback force;

[0012] The control processing module is used to calculate the key feedback force parameters based on the optimization algorithm and send adjustment commands to the feedback force adjustment module through control signals.

[0013] The user configuration interface is used for users to input target feedback parameters, including feedback mode and feedback force curve;

[0014] Output device for applying feedback force to the key shaft via an inductor shaft assembly.

[0015] Preferably, the feedback force adjustment module is used to generate a combined feedback force of electromagnetic force and mechanical force, the combined feedback force including an electromagnetic force determined by the coil current and the button displacement, and a mechanical force determined by the elastic element and the damping element.

[0016] Preferably, the electromagnetic force is generated by controlling the coil current through a PWM signal, and the magnitude of the coil current is calculated and adjusted in real time by the control processing module.

[0017] Preferably, the control processing module calculates the feedback force parameters based on an optimization objective function, which is used to minimize the deviation between the target feedback force and the actual feedback force, while optimizing the dynamic response and energy consumption of the feedback system.

[0018] Preferably, the optimization objective function balances the following objectives through weighting coefficients: the squared error between the target feedback force and the actual feedback force, the squared deviation of the button motion response, and the total system energy consumption.

[0019] Preferably, the user configuration interface is used to support the selection of multiple feedback modes, including linear mode, non-linear mode and paragraph mode, and supports single-key or regional adjustment.

[0020] Preferably, the feedback force in the nonlinear mode is determined by both the button displacement and the pressing speed, and is generated according to the feedback curve set by the user.

[0021] Preferably, the mechanical force includes an elastic force provided by an elastic element and a damping force provided by a damping element, the magnitudes of which are determined by the control processing module by adjusting the elastic coefficient and the damping coefficient.

[0022] Preferably, the output device includes a magnetic core component, an induction coil, and a key shaft. The magnetic core component generates a magnetic field change in the induction coil as the key shaft moves, thereby generating an induction signal.

[0023] Preferably, the control processing module dynamically calculates feedback parameters and adjusts the current signal and mechanical parameters of the feedback force adjustment module in real time based on the key press data collected by the sensor module and the target feedback force curve input by the user.

[0024] This invention provides an adjustable force feedback system for keyboard keys. It has the following advantages:

[0025] 1. This invention employs a technical solution combining electromagnetic and mechanical feedback forces to achieve real-time dynamic adjustment of button feedback force. By controlling the magnitude of the electromagnetic force and the proportional distribution of the mechanical force, it achieves precise control over the tactile feedback and sensitivity of the buttons. Compared to existing technologies that rely on either a single electromagnetic or mechanical force generation method, this invention solves the problem of insufficient flexibility in button feedback force and its inability to adapt to various usage scenarios. This invention can provide adaptable button feel for multiple scenarios by adjusting the driving current of the electromagnetic coil in real time, achieving personalized feedback optimization, especially in gaming or office scenarios.

[0026] 2. This invention employs an optimization algorithm combined with real-time data input from a sensor module to dynamically calculate feedback force parameters. By optimizing the objective function to balance feedback accuracy, response speed, and energy consumption, it achieves improved button feedback performance and energy efficiency. Existing technologies often neglect energy consumption optimization or dynamic response delay issues; this invention, however, solves the problems of feedback adjustment lag and high energy consumption through intelligent algorithms, making button operation more efficient and energy-saving.

[0027] 3. This invention combines PWM signal control technology and nonlinear elastic design to dynamically adjust the proportion of electromagnetic and mechanical forces at different stages of the button travel, achieving multi-stage tactile feedback and bottoming-out sensation. This results in a more personalized user experience. Existing technologies have relatively fixed tactile feedback simulations that cannot be flexibly adjusted. This invention solves the problem of a single and unvarnished button travel feedback mode, meeting the needs of different scenarios such as office work and gaming.

[0028] 4. This invention uses a predictive control algorithm to pre-calculate the movement state of the buttons and combines this with historical data provided by the sensor module to achieve pre-optimization of the feedback force parameters. This results in faster and smoother feedback force generation. Unlike the passive response of existing technologies that rely on button states, this invention solves the problems of slow feedback force adjustment and inconsistent user experience, providing a superior solution for high-frequency button operation scenarios. Attached Figure Description

[0029] Figure 1 This is a schematic diagram of the system framework of the present invention;

[0030] Figure 2 This is a schematic diagram of the force feedback process of the present invention. Detailed Implementation

[0031] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0032] Example:

[0033] Please see the appendix Figure 1 and attached Figure 2 This invention provides an adjustable force feedback system for a keyboard, including...

[0034] Inductive shaft assembly: Composed of an induction coil, a magnetic core component, and a button shaft. The movement of the magnetic core component senses changes in the magnetic field, providing the basis for generating electromagnetic feedback force. This force is used to sense the button's press depth, pressure, and speed, providing the initial physical signal conversion capability.

[0035] Sensor module: Integrates pressure, speed, and displacement sensors. It monitors the physical state of the buttons in real time, including pressure applied, speed of movement, and travel distance.

[0036] Feedback force adjustment module: Includes PWM control circuit and mechanical rebound device to adjust electromagnetic feedback force according to input signal, outputting precise button feedback. It can generate combined electromagnetic and mechanical force feedback to meet user needs in various scenarios.

[0037] Control processing module: The core of the system, responsible for optimizing feedback force parameters. It employs optimization algorithms to transform the user-input target feedback force curve into specific control signals, and includes a microcontroller (MCU) and a feedback calculation algorithm module.

[0038] User configuration interface: Provides a convenient configuration interface through which users can adjust the feedback force, sensitivity, and feedback curve of each button. Users can select different feedback modes and set personalized parameters for single buttons or areas through this module.

[0039] Output device: includes key shaft, rebound mechanism, and feedback force transmission mechanism. The calculated feedback force is applied to the key for user perception.

[0040] The generation of electromagnetic feedback force is a crucial step in an adjustable force feedback system. This step is closely related to the control processing module, the feedback force adjustment module, and the inductor shaft assembly, and relies on real-time data input from the sensor module. Through optimization algorithms, the feedback parameters are calculated, and the electromagnetic feedback force is determined by factors such as coil current and button displacement.

[0041] The basic principle of electromagnetic feedback force generation is based on Ampere's law and the law of action of Lorentz force.

[0042] The electromagnetic feedback force is generated by the combined effect of the current and magnetic field strength within the induction coil, and its magnitude is related to the button's displacement and the control signal. The feedback force adjustment module adjusts the instantaneous current intensity of the coil via a PWM signal, thereby changing the magnitude of the electromagnetic force and achieving dynamic adjustment. The control signal is generated by the control processing module based on an optimization algorithm; the specific calculation process combines the user's target feedback parameters and the real-time physical state of the button.

[0043] The magnetic core component is embedded in the button shaft, forming a complete inductor shaft structure with the inductor coil. When the user presses the button, the magnetic core component moves along the button travel direction, causing a change in the magnetic flux within the coil. At this time, the electromagnetic force generated by the current in the inductor coil changes with the button displacement, and is thus applied to the user through the button shaft.

[0044] Electromagnetic feedback force can be expressed by the following formula:

[0045] F elec (t)=k1·I(t)·B(t)

[0046] in:

[0047] F elec (t): Real-time electromagnetic feedback force, in Newtons (N);

[0048] k1: The structural proportionality coefficient of the inductor shaft, which is related to factors such as the number of coil turns and the properties of the magnetic core material;

[0049] I(t): Instantaneous current intensity in the coil, measured in amperes (A);

[0050] B(t): Magnetic flux density inside the coil, measured in Tesla (T).

[0051] The magnetic induction intensity B(t) is linearly related to the key displacement x(t).

[0052] For example, as the magnetic core component moves during the button's travel, it changes the distribution of the magnetic field within the coil. Generally, the magnitude of the magnetic induction intensity can be approximated as:

[0053] B(t) = k²·x(t)

[0054] in:

[0055] k2: Magnetic induction proportionality coefficient, with units of Tesla / meter (T / m), which is related to the geometry and material properties of the magnetic core component;

[0056] x(t): Real-time displacement of the button, in meters (m).

[0057] Substituting the above formula into the expression for electromagnetic force, the electromagnetic feedback force is further expressed as:

[0058] F elec (t)=k1·k2·I(t)·x(t)

[0059] In this case, the magnitude of the electromagnetic force is linearly related to the key displacement and the coil current. This formula reflects the characteristic that the greater the key displacement, the stronger the feedback force, and is suitable for key feedback modes that require a clear tactile feedback.

[0060] The instantaneous current I(t) in the coil is controlled by a PWM signal.

[0061] The PWM signal is generated by the control processing module, specifically including duty cycle adjustment and frequency setting. Alternatively, the duty cycle α represents the proportion of the high-level time of the PWM signal within one cycle, ranging from [0,1]. The relationship between instantaneous current and duty cycle can be expressed as:

[0062] I(t) = α·I max

[0063] in:

[0064] I(t): Instantaneous current intensity in the coil, measured in amperes (A);

[0065] α: Duty cycle of the PWM signal;

[0066] I max : The maximum value of the coil current, measured in amperes (A).

[0067] Based on the aforementioned relationship between magnetic induction intensity and button displacement, the final expression for the electromagnetic feedback force is:

[0068] F elec(t)=k1·k2·α·I max ·x(t)

[0069] The duty cycle of the PWM signal is dynamically adjusted by the control processing module to meet the feedback requirements in different scenarios.

[0070] For example, in game mode, the control processing module will prioritize increasing the duty cycle α, while simultaneously increasing the maximum current I. max The value of α is adjusted to enhance the effect of electromagnetic force, adapting to the needs of rapid, continuous key presses. In office mode, the duty cycle α and the maximum current I... max It will be appropriately reduced to provide a softer button feedback.

[0071] The inductance parameters of the coil affect the rate of change of the electromagnetic feedback force and the accuracy of the response.

[0072] To ensure a rapid response to feedback force, the number of coil turns is typically designed to be between 500 and 1500. The DC resistance R of the coil limits the maximum current I. max Therefore, it is necessary to rationally select the coil material and cross-sectional area based on the energy efficiency optimization scheme. Generally, using highly conductive copper wire can effectively reduce resistance, thereby reducing energy loss.

[0073] To improve the stability of the electromagnetic force, the coil current signal is dynamically adjusted in conjunction with the button displacement and speed.

[0074] For example, when the key press speed is high, the feedback force will be appropriately enhanced according to the speed compensation algorithm to reduce user input errors. This dynamic adjustment can be achieved through the following formula:

[0075]

[0076] in:

[0077] k4: Speed ​​compensation coefficient, which is related to button feedback sensitivity;

[0078] The real-time speed of the button press, measured in meters per second (m / s).

[0079] In the electromagnetic feedback force generation step, the aforementioned formulas and implementation methods provide theoretical support and a practical approach for the dynamic adjustment of the feedback force. The control module generates a PWM signal to control the coil current by combining the real-time state of the button and the target feedback force curve, thereby achieving real-time adjustment of the feedback force. The coil current, magnetic induction intensity, button displacement, and velocity jointly determine the magnitude and trend of the feedback force, providing users with a precise and adjustable button force feedback experience.

[0080] The generation of mechanical feedback force is a crucial component of an adjustable force feedback system for buttons. This step, in conjunction with the generation of electromagnetic feedback force, enables dynamic adjustment and precise control of the button feedback force. The generation of mechanical feedback force primarily relies on elastic and damping elements, providing stability and versatility to the button feedback characteristics by offering rebound force and vibration reduction.

[0081] The mechanical feedback force consists of both elastic force and damping force, and its calculation is based on the real-time displacement and velocity of the button.

[0082] Generally, the elastic force is mainly generated by the spring structure to provide the rebound characteristics of the button. The damping force is provided by the damping element, which acts during the button's movement to suppress excess vibration and provide resistance. The combination of these two forces allows the button to exhibit adjustable tactile feedback and feel under different pressing conditions.

[0083] Mechanical feedback force F mech The expression for (t) is:

[0084] F mech (t)=F spring (t)+F damp (t)

[0085] in:

[0086] F spring (t): Elastic force generated by the elastic element;

[0087] F damp (t): Damping force generated by the damping element.

[0088] Elastic force F spring (t) is determined by the displacement of the key.

[0089] Elastic force can be expressed as:

[0090] F spring (t)=-k3x(t)

[0091] in:

[0092] k3: Spring constant, measured in Newtons per meter (N / m), which is related to the material and design parameters of the spring;

[0093] x(t): Real-time displacement of the button, in meters (m).

[0094] Generally, the range of values ​​for the elasticity coefficient k3 is designed based on the usage scenario of the button. For example:

[0095] In game mode, k3 is typically higher to provide stronger rebound.

[0096] In office mode, the K3 is usually set to a lower setting to reduce fatigue from keystrokes.

[0097] As an option, the spring design can employ either a linear or non-linear spring. A linear spring provides a constant spring constant throughout the key travel, suitable for applications requiring smooth feedback. A non-linear spring, on the other hand, has a spring constant that varies with the displacement, providing different tactile feedback at different stages of the key travel. For example, at the initial stage of the key travel, a non-linear spring has a lower spring constant, providing a gentle initial press experience; towards the end of the key travel, the spring constant increases, enhancing the bottom support of the key.

[0098] In this embodiment, the damping force F damp (t) is related to the movement speed of the button.

[0099] The damping force can be expressed as:

[0100]

[0101] in:

[0102] c: Damping coefficient, measured in Newton-seconds per meter (N·s / m), which is related to the damping material and structural design;

[0103] The real-time speed of the button press, measured in meters per second (m / s).

[0104] Alternatively, the damping coefficient c can be dynamically adjusted to suit different button feedback modes. For example:

[0105] In scenarios involving rapid key presses, reducing the value of 'c' makes the key rebound faster.

[0106] In low-frequency key press scenarios, appropriately increasing the value of c can reduce unnecessary key vibration.

[0107] Specifically, the damping element can take the form of liquid damping, rubber damping, or magnetic damping. For example, in some embodiments, a rubber damping element can be integrated into the bottom of the key shaft, providing motion damping through the internal resistance characteristics of the material. In another possible design, the magnetic damping element achieves non-contact damping through the eddy current effect generated by the coil; this design can reduce mechanical wear and extend system life.

[0108] In some embodiments, the combination of elastic force and damping force enables the simulation of segmentation.

[0109] Specifically, by adjusting the elastic coefficient k3 and damping coefficient c at different stages of the button travel, multiple stages of feedback force variation can be achieved. For example:

[0110] During the initial stage of the button travel, the feedback force is light, providing a gentle triggering feel;

[0111] During the middle stage of the stroke, the feedback force gradually increases, simulating the tactile feedback of a mechanical keyboard;

[0112] At the end of the stroke, the feedback force increases rapidly, providing a clear bottoming sensation.

[0113] To achieve the above functions, the control processing module can dynamically adjust k3 and c based on the user's feedback curve settings. In some embodiments, a non-linear adjustment algorithm is used to optimize the distribution of tactile feedback, ensuring that the buttons maintain stable mechanical characteristics even during rapid operation.

[0114] As one implementation method, the mechanical feedback force generation step can work in conjunction with the electromagnetic feedback force generation step.

[0115] For example, in game mode, the combination of electromagnetic and mechanical forces can provide a fast and powerful button feedback experience. Specifically, in the initial stage of button pressing, mechanical elasticity dominates the generation of feedback force; in the middle stage of button travel, electromagnetic and mechanical forces work together to enhance the tactile feedback of the button; and in the button release stage, damping force plays a major role in smoothing the button rebound process.

[0116] In office mode, mechanical force can play a major role. By reducing the elastic coefficient k3 and damping coefficient c, a relaxed and stable button operation experience can be achieved.

[0117] In this embodiment, in order to further optimize the characteristics of the mechanical feedback force, the material and structural design of the spring and damping elements can be selected according to user needs.

[0118] For example, springs can be made of high-strength alloys to increase durability, or composite materials to provide adjustable nonlinear elastic characteristics. Damping elements can use different combinations of materials, such as rubber-metal composites, to simultaneously meet the requirements of vibration reduction and wear resistance.

[0119] The mechanical feedback force generation step provides fundamental support for button feedback force through the synergistic effect of elastic and damping forces. Combined with the dynamic adjustment of electromagnetic feedback force, the generation of mechanical feedback force enables this invention to meet the button operation needs in various scenarios, providing users with a rich and personalized feedback experience. Through the optimized design of springs and damping elements, this invention can also significantly improve the durability and comfort of the buttons.

[0120] In the "Adjustable Force Feedback System for Keyboard" of this invention, dynamic feedback optimization is a core function of the system, mainly achieving precise control of feedback through the comprehensive adjustment of electromagnetic and mechanical feedback forces. The dynamic feedback optimization steps are closely related to the control processing module and rely on real-time key status data provided by the sensor module and the target feedback curve input by the user. Based on the aforementioned generation of electromagnetic and mechanical feedback forces, this step achieves real-time dynamic adjustment of the feedback force through algorithm optimization, ensuring that the key feedback performance meets the user's set requirements.

[0121] In this embodiment, dynamic feedback optimization is achieved by establishing an optimization objective function to calculate the feedback force parameters.

[0122] Generally, optimizing an objective function requires simultaneously considering the accuracy of button feedback, dynamic response speed, and energy efficiency. These objectives may conflict; for example, increasing response speed might lead to increased energy consumption. Therefore, this invention constructs a multi-objective optimization function to comprehensively balance the relationship between feedback performance and energy consumption. The form of the optimization objective function is as follows:

[0123]

[0124] in:

[0125] J: Optimize the value of the objective function;

[0126] F: The total feedback force actually generated, in Newtons (N);

[0127] F target User-defined target feedback force, in Newtons (N);

[0128] The real-time speed of the button press, measured in meters per second (m / s);

[0129] Target speed, in meters per second (m / s);

[0130] I: Current in the electromagnetic coil, measured in amperes (A);

[0131] R: The resistance of the coil, measured in ohms (Ω);

[0132] c: Damping coefficient, in Newton-seconds per meter (N·s / m);

[0133] λ1, λ2, λ3: Weighting coefficients, used to adjust the balance between feedback force error, velocity response, and energy consumption optimization, respectively.

[0134] Alternatively, the values ​​of the aforementioned weighting coefficients can be flexibly set according to the application scenario. For example:

[0135] In game mode, the value of λ2 can be increased to prioritize meeting the dynamic response requirements of the buttons;

[0136] In office mode, the value of λ3 can be increased to reduce energy consumption during system operation.

[0137] Specifically, dynamic feedback optimization relies on the Hamiltonian optimization method to calculate the optimal feedback parameters.

[0138] Solving the optimization problem is based on the system's Hamiltonian function, which is constructed from the Lagrange function. The Hamiltonian function has the following form:

[0139]

[0140] in:

[0141] H: The Hamiltonian function of the system;

[0142] L: The Lagrangian function of the system, expressed as L = TU;

[0143] T: The kinetic energy of the button's movement, expressed as... Where m is the equivalent mass of the button;

[0144] U: The potential energy of the force field feedback from the button, expressed as U=∫Fdx.

[0145] Using the Hamiltonian function, the feedback force control equation for the button can be further obtained:

[0146]

[0147] in It refers to generalized momentum.

[0148] In one possible implementation, the electromagnetic feedback force F can be determined by numerically solving the aforementioned governing equations. elec and mechanical feedback force F mech The optimal parameters are determined. For example, when the key displacement is small, electromagnetic force can dominate; while at the end of the key travel, mechanical elastic force can provide stronger support.

[0149] In this embodiment, the optimization process is dynamically completed by combining real-time data provided by the sensor module and the target curve input by the user.

[0150] Specifically, the optimization algorithm requires the following input data:

[0151] The button states collected by the sensor module include displacement x(t) and velocity. and the external force F applied by the user ext (t).

[0152] The user configuration interface provides target feedback parameters, including the target feedback force curve F. target (x,v) and target velocity

[0153] Alternatively, the computation cycle of the optimization algorithm can be dynamically adjusted based on the usage scenario of the buttons. For example:

[0154] In high-frequency button scenarios, the algorithm's calculation cycle can be shortened to ensure that the feedback force can quickly respond to user operations;

[0155] In low-frequency button press scenarios, the calculation cycle can be appropriately extended to reduce the system's computational load and energy consumption.

[0156] In some embodiments, dynamic feedback optimization further includes adjusting the ratio of electromagnetic feedback force to mechanical feedback force.

[0157] For example, by adjusting the proportion of electromagnetic force, multi-stage tactile feedback can be achieved on buttons. Specifically:

[0158] In the initial stage of the button travel, the electromagnetic force is relatively small, and the mechanical force dominates the generation of feedback force, providing a gentle triggering sensation;

[0159] During the middle stage of the key travel, electromagnetic and mechanical forces work together to enhance the tactile feedback of the key.

[0160] At the end of the key travel, the electromagnetic force gradually increases, providing a clearer bottoming-out feel to the key.

[0161] As one implementation method, the control processing module can adjust the intensity of the electromagnetic force and the parameters of the mechanical force in real time based on the output of the optimization algorithm. For example, in office mode, the optimization algorithm can prioritize reducing the proportion of electromagnetic force to reduce system energy consumption; while in game mode, the intensity of electromagnetic force can be increased to meet the operation requirements of rapid key presses.

[0162] In this embodiment, to further improve the efficiency of optimization, dynamic feedback optimization can be combined with predictive control algorithms for calculation.

[0163] For example, by analyzing historical trends in sensor data, the next movement of a button can be predicted. This allows for the pre-calculation of feedback parameters, shortening response time. The core of predictive control algorithms is constructing a dynamic model of the button's movement state, which takes the form:

[0164]

[0165] in:

[0166] x(t+Δt): Predicted key displacement;

[0167] Δt time step;

[0168] Real-time acceleration of the button.

[0169] Dynamic feedback optimization, through a combination of multi-objective optimization functions, Hamiltonian control methods, and predictive control algorithms, ensures that real-time adjustment of button feedback force achieves a comprehensive performance of high precision, fast response, and energy efficiency. By linking with the sensor module and control processing module, the optimization steps of this invention can flexibly adapt to different user needs and provide precise and stable control support for button force feedback.

[0170] In this embodiment, the implementation steps start with the input of the user configuration interface, and the feedback force is output in real time through the calculation of the control processing module.

[0171] Typically, users input target feedback parameters through the user configuration interface module. These parameters include the target feedback force curve, button mode, sensitivity settings, and more. The sensor module collects the physical state data of the buttons in real time, providing a basis for dynamic adjustment of the feedback force.

[0172] Alternatively, the user-configured target feedback curve can take the form of a linear or non-linear curve. For example, a linear curve is used for the smooth feedback requirements of office mode; a non-linear curve is suitable for the enhanced segmentation requirements of game mode.

[0173] Specifically, the sensor module measures the real-time state of the button, including the button displacement x(t) and velocity. and the external force F applied by the user ext (t). Among them, the button displacement is detected by a high-precision displacement sensor, the speed is obtained by calculating the time derivative of the displacement, and the user's external force is directly measured by a pressure sensor.

[0174] In one possible implementation, the control processing module performs optimization calculations based on user input and sensor data.

[0175] First, the control module preprocesses the data input from the sensors, filtering out noise interference and calibrating the signals. Then, it constructs a feedback force optimization objective function, which comprehensively considers the accuracy of the feedback force, the dynamic response of the buttons, and energy efficiency.

[0176] The expression for the optimization objective function is:

[0177]

[0178] in:

[0179] F is the actual feedback force, which is generated by the superposition of electromagnetic feedback force and mechanical feedback force;

[0180] Ftarget Feedback on user-defined goals;

[0181] The real-time speed of the key press;

[0182] Target speed for the user;

[0183] I is the coil current, R is the coil resistance, and c is the damping coefficient;

[0184] λ1, λ2, and λ3 are the weight coefficients of the optimization objective.

[0185] Generally, the choice of weighting coefficients depends on the application scenario of the buttons. For example, in gaming mode, λ2 has a higher weight to prioritize ensuring the dynamic response speed of the buttons. In office mode, the value of λ3 is appropriately increased to reduce energy consumption.

[0186] In this embodiment, the generation steps of electromagnetic feedback force and mechanical feedback force are combined with the results of optimized calculations.

[0187] The electromagnetic feedback force is controlled by a feedback force adjustment module, which adjusts the coil current I(t) in real time via a PWM signal. The magnitude of the electromagnetic force is related to the button displacement x(t), the magnetic induction intensity B(t), and the current intensity I(t), and its expression is:

[0188] F elec (t)=k1·k2·I(t)·x(t)

[0189] in:

[0190] k1 and k2 are the proportionality coefficients of the system, which are related to the coil design and the magnetic core material.

[0191] I(t) is adjusted by the control module through the duty cycle to meet the output of the optimized calculation.

[0192] The mechanical feedback force is generated by both elastic force and damping force, and its total force formula is:

[0193]

[0194] in:

[0195] k3 is the spring constant, which is related to the material and shape of the spring;

[0196] c is the damping coefficient, which is related to the design parameters of the damping material or damping device.

[0197] As an option, the parameters of the mechanical feedback force can be dynamically adjusted based on the optimization results. For example, when the button displacement is large, the elastic force F can be increased. spring The proportion of (t); during the button release phase, increase the damping force F.damp (t) is used to smooth the rebound process of the key.

[0198] Specifically, the total output of the feedback force is generated by the superposition of electromagnetic feedback force and mechanical feedback force.

[0199] The total output of the feedback force can be expressed as:

[0200] F total (t)=F elec (t)+F mech (t)

[0201] In some embodiments, to achieve a sense of multiple paragraphs, the control module dynamically adjusts F. elec (t) and F mech The ratio of (t). For example, in the initial stage of the key travel, the feedback force is mainly mechanical elastic force; in the middle stage of the travel, the electromagnetic force gradually increases, providing a clear tactile feedback; at the end of the travel, the electromagnetic force and mechanical force work together to enhance the bottoming-out feel of the key.

[0202] In one possible implementation, the control processing module further optimizes the feedback parameters by combining predictive control algorithms.

[0203] By collecting historical data from the sensor module, the control module can predict the next movement of the button and adjust the feedback force parameters in advance. For example, the predicted displacement x(t+Δt) of the button can be calculated using the following formula:

[0204]

[0205] in:

[0206] Δt is the time step;

[0207] This refers to the real-time acceleration of the button press.

[0208] Predictive control enables the generation of feedback force to respond more quickly to user operations, effectively improving the dynamic performance of buttons.

[0209] Ultimately, the implementation process culminates in the physical output of the feedback force.

[0210] The output device transmits the total feedback force to the user via the button shaft, completing the transmission of the mechanical signal. In office mode, the output feedback force is gentler; in game mode, the feedback force is strong and the response is fast. Through the above implementation steps, the connection between each module is clear, and the generation and optimization of feedback force can be completed efficiently, ensuring that the system's performance meets the needs of different scenarios.

[0211] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A keyboard key adjustable force feedback system, characterized in that, include, The inductive shaft assembly is used to sense the pressed state of the button and generate feedback force by acting on the button shaft through electromagnetic force; The sensor module is used to collect information on the pressure applied to the button, the speed of the press, and the displacement of the press. The feedback force adjustment module is used to coordinate the adjustment of electromagnetic force and mechanical force according to the target feedback force; The control processing module is used to calculate the key feedback force parameters based on the optimization algorithm and send adjustment commands to the feedback force adjustment module through control signals. The user configuration interface is used for users to input target feedback parameters, including feedback mode and feedback force curve; Output device for applying feedback force to the key shaft via the inductor shaft assembly; The control processing module calculates the feedback force parameters based on an optimization objective function. The optimization objective function is used to minimize the deviation between the target feedback force and the actual feedback force, while optimizing the dynamic response and energy consumption of the feedback system. The optimization objective function balances the following objectives through weighting coefficients: the squared error between the target feedback force and the actual feedback force, the squared deviation of the button motion response, and the total system energy consumption; The user configuration interface is used to support the selection of multiple feedback modes, including linear mode, non-linear mode and paragraph mode, and supports single-key or regional adjustment. The feedback force in the nonlinear mode is determined by both the button displacement and the pressing speed, and is generated according to the feedback curve set by the user.

2. The adjustable force feedback system for the keyboard according to claim 1, characterized in that, The feedback force adjustment module is used to generate a combined feedback force of electromagnetic force and mechanical force. The combined feedback force includes an electromagnetic force determined by the coil current and the button displacement, and a mechanical force determined by the elastic element and the damping element.

3. The adjustable force feedback system for the keyboard according to claim 1, characterized in that, The electromagnetic force is generated by controlling the coil current through a PWM signal, and the magnitude of the coil current is calculated and adjusted in real time by the control processing module.

4. The adjustable force feedback system for the keyboard according to claim 1, characterized in that, The mechanical force includes elastic force provided by elastic elements and damping force provided by damping elements. The magnitudes of the elastic force and damping force are determined by the control processing module by adjusting the elastic coefficient and damping coefficient.

5. The adjustable force feedback system for the keyboard according to claim 1, characterized in that, The output device includes a magnetic core component, an induction coil, and a key shaft. The magnetic core component generates a magnetic field change in the induction coil as the key shaft moves, thereby generating an induction signal.

6. The adjustable force feedback system for the keyboard according to claim 1, characterized in that, The control processing module dynamically calculates feedback parameters and adjusts the current signal and mechanical parameters of the feedback force adjustment module in real time based on the key press data collected by the sensor module and the target feedback force curve input by the user.

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