A method and system for adaptive adjustment of a vehicle suspension based on motion sickness dose value

Abstract

The present application relates to the technical field of vehicle comfort control, and discloses a vehicle suspension adaptive adjustment method and system based on motion sickness dose value, which comprises the following steps: collecting three-axis acceleration signals in real time, performing frequency weighting filtering according to a standard, and then calculating a motion sickness dose value MSDV-20 by discrete integration with a 20-second sliding window; comparing the MSDV-20 with a preset threshold value to determine a risk level, and identifying a vibration type such as longitudinal / lateral swing dominance, vertical bumping dominance or a compound type through three-axis effective value comparison; when the risk level is not lower than level 2, performing differentiated intervention according to the risk level and the vibration dominant type: increasing rebound damping when the swing is dominant, and reducing rebound damping when the bumping is dominant; calculating an effect score E after the intervention, and driving strategy fine-tuning, upgrading or switching to form a closed-loop adaptive adjustment. The present application realizes real-time quantification of motion sickness risk, differentiated suspension adjustment and closed-loop self-iteration, and is easy to mass-produce and land.

Description

Technical Field

[0001] This invention relates to the field of vehicle comfort control technology, and more specifically, to a vehicle suspension adaptive adjustment method and system based on motion sickness dose values. Background Technology

[0002] Motion sickness, commonly known as "car sickness," is a series of physiological discomfort reactions caused by a conflict between motion signals perceived by the vestibular system and visual and proprioceptive information. Studies have shown that low-frequency vehicle vibrations (0.1–0.5 Hz) are the most significant cause of motion sickness, with longitudinal and lateral low-frequency accelerations being the primary sources, while vertical vibrations at approximately 4–8 Hz have the greatest impact on discomfort. The international standard ISO 2631-1-1997 defines the Motion Sickness Dose Value (MSDV) as an objective physical indicator quantifying human exposure to motion sickness. However, existing technologies have the following limitations:

[0003] First, traditional MSDV is a global cumulative amount, which is integrated from the start of the trip to the current time. Its value increases monotonically with the travel time, which does not have real-time characteristics, cannot represent the current short-term risk, and cannot be compared horizontally between trips of different durations.

[0004] Secondly, existing motion sickness intervention solutions are disconnected from the MSDV (Motion Sickness and Dust) index. Some solutions use MSDV as the control target, but they are mostly focused on the low-level control of the power domain and rely on torque signals, which cannot cover the motion sickness caused by road bumps during constant speed driving. Other solutions use data-driven methods such as neural networks, but their prediction results lack a clear mapping relationship with physical indicators such as ISO 2631, and their generalization ability is limited.

[0005] Furthermore, existing suspension damping adjustment strategies do not fully consider the differences in vibration frequency and direction. Longitudinal / lateral low-frequency swaying accumulates into a dizzying effect through continuous low-frequency stimulation of the vestibular system, while vertical mid-frequency jolts directly cause physical discomfort through impact transmission. The damping adjustment directions that should be adopted for these two are significantly different, but existing solutions fail to implement differentiated suspension control strategies based on vibration characteristics. Summary of the Invention

[0006] To address at least one of the aforementioned problems, the present invention first provides a vehicle suspension adaptive adjustment method based on motion sickness dose values, comprising the following steps:

[0007] The vehicle uses an onboard six-axis IMU to collect three-axis acceleration signals in real time during the vehicle's movement at a preset sampling frequency.

[0008] According to the ISO 2631-1-1997 standard a frequency-weighted transfer function, performing digital filtering and weighting processing on the collected acceleration signal to obtain a frequency-weighted acceleration time-history signal;

[0009] using a sliding time window with the current moment as the end point and a preset width W, performing discrete integration on the square of the frequency-weighted acceleration within the window and then taking the square root, to calculate the sliding window motion sickness dose value MSDV-W in real time with a preset step size;

[0010] comparing MSDV-W with a plurality of preset increasing thresholds to determine the current risk level;

[0011] determining whether the risk level is greater than or equal to a preset intervention trigger level, if yes, selecting and executing an intervention measure from a preset multi-modal intervention strategy matrix according to the risk level and the current dominant vibration type; if no, maintaining the current state and continuing monitoring.

[0012] Optionally, the preset width W is 20 seconds, and the preset step size is 1 second;

[0013] The sliding window motion sickness dose value MSDV-W is calculated according to the following discretization formula:

[0014]

[0015] wherein, is the sampling interval, is the total number of sampling points within the window, is the frequency-weighted acceleration value at the sampling moment, is the current output moment.

[0016] Optionally, the step of comparing MSDV-W with a plurality of preset increasing thresholds to determine the current risk level specifically comprises:

[0017] comparing MSDV-W with five preset increasing thresholds TH1, TH2, TH3, TH4, TH5:

[0018] If MSDV-W<TH1, it is determined as level 0;

[0019] If TH1≤MSDV-W<TH2, it is determined as level 1;

[0020] If TH2≤MSDV-W<TH3, it is determined as level 2;

[0021] If TH3≤MSDV-W<TH4, it is determined as level 3;

[0022] If TH4≤MSDV-W<TH5, it is determined as level 4;

[0023] The preset intervention trigger level is level 2;

[0024] It also includes the step of identifying the current dominant vibration type:

[0025] By comparing the effective values ​​of the triaxial IMU acceleration signals after frequency-weighted filtering, the dominant type of the current vibration can be identified.

[0026] The dominant vibration types include longitudinal swaying, lateral swaying, vertical turbulence, and a combination thereof.

[0027] Optionally, after the vehicle is turned off, a trip comfort report is automatically generated based on the full-journey MSDV-W time-series data and intervention records stored in the memory. The report includes the full-journey MSDV-W peak value, MSDV-W mean value, duration percentage of each risk level, and statistics on the effectiveness of the intervention strategy.

[0028] Optionally, a hierarchical visualization output step is also included:

[0029] Based on the risk level, a corresponding display instruction is generated, and the current motion sickness risk status is displayed in real time on the vehicle central control display screen in the form of dynamic curves, color changes, emoticons and text prompts.

[0030] The color of the dynamic curve gradually changes from green to red as the risk level increases.

[0031] Optionally, the intervention includes suspension damping adjustment:

[0032] Determine whether the current dominant vibration type is longitudinal sway or lateral sway. If yes, increase the rebound damping. If no, determine whether the current dominant vibration type is vertical turbulence. If yes, decrease the rebound damping. If no, determine that the current dominant vibration type is a combination type and keep the current damping state unchanged.

[0033] The adjustment range for increasing rebound damping is +15% to +50%, and the adjustment range for decreasing rebound damping is -10% to -30%.

[0034] The suspension damping adjustment is performed by sending a PWM control signal to the shock absorber solenoid valve, and the adjustment process is completed linearly and gradually within 0.5 to 1.5 seconds.

[0035] Optionally, the intervention may also include audio-induced intervention:

[0036] Determine whether the risk level is greater than or equal to level 2. If so, play background music with a rhythm of 2.5~5Hz through the vehicle audio system; otherwise, do not trigger audio-guided intervention.

[0037] Optionally, it also includes steps for intervention effectiveness evaluation and strategy iteration:

[0038] Within the time window following the implementation of the intervention, the changing trend of the MSDV-W value was continuously monitored, and the intervention effect score E was calculated.

[0039] If E is less than the first preset threshold, the strategy is deemed effective and the current strategy parameter combination is recorded in the strategy effective library. If not, the strategy is deemed greater than the second preset threshold. If so, the strategy is deemed invalid and a strategy upgrade is immediately triggered, adjusting the suspension damping to the maximum or minimum usable value while displaying a deceleration suggestion on the central control screen. If not, the effect is deemed insufficient, triggering a strategy fine-tuning to keep the suspension parameters unchanged.

[0040] The formula for calculating the intervention effect score E is:

[0041]

[0042] in, and Here, T is the evaluation time window, and RMS is the root mean square value of the vehicle's vertical acceleration. The root mean square value of the vehicle's vertical acceleration within the time window following the implementation of the intervention measures; The root mean square value of the vehicle's vertical acceleration within the time window prior to the implementation of the intervention;

[0043] If the strategy remains ineffective after two evaluation cycles following fine-tuning, the intervention intensity will be increased, with the damping adjustment range increased by 10 percentage points.

[0044] Optionally, a mode exit step may also be included:

[0045] Determine whether the risk level of MSDV-W drops to level 1 or below within a preset number of assessment cycles. If so, exit the motion sickness comfort control mode, and the damping linearly recovers to the pre-intervention value within a preset time, and enter the silent monitoring period; if not, maintain the current intervention status.

[0046] Alternatively, determine whether the MSDV-W decreases by more than a preset threshold and whether the rate of change remains within a preset range within a subsequent preset time. If so, maintain the current intervention parameters and exit after the risk is further reduced; otherwise, maintain the current intervention status.

[0047] Alternatively, determine whether the suspension damping adjustment has reached its physical limit and whether the MSDV-W continues to rise. If so, stop the suspension damping adjustment, maintain the current damping value, and trigger a speed reduction suggestion; if not, maintain the current intervention state.

[0048] Compared with the prior art, the beneficial technical effects of the present invention are as follows:

[0049] 1. By introducing a 20-second fixed time window sliding integral mechanism (i.e., MSDV-20), the calculation of MSDV is upgraded from post-hoc statistics to real-time streaming calculation updated every second, eliminating the interference of travel duration on the numerical value, and making the monitoring of motion sickness risk truly real-time, comparable and dynamic sensitive. At the same time, MSDV-20 is used as the core feedback variable of the closed-loop control system to directly drive the active adjustment of suspension damping and the coordinated execution of audio intervention, upgrading motion sickness dose from a post-hoc assessment indicator to a real-time control target.

[0050] 2. By comparing the effective values ​​of the IMU three-axis acceleration signals, different vibration types such as longitudinal / lateral low-frequency swaying and vertical mid-frequency bumps can be accurately identified, and corresponding damping control strategies can be implemented. That is, when low-frequency swaying is dominant, the rebound damping is increased (+15%~+50%) to suppress the cumulative effect of vehicle body swaying, and when vertical bumps are dominant, the rebound damping is decreased (-10%~-30%) to absorb the peak impact of the road surface, thus avoiding the failure problem of traditional one-size-fits-all damping adjustment.

[0051] 3. The real-time fine-tuning, upgrading or switching of the strategy is driven by the intervention effect score E (which comprehensively considers the MSDV-20 change rate and the RMS change rate of the vehicle vertical acceleration). Clear mode exit conditions (risk downgrade, effective stability, and boundary reaching) and a mechanism to prevent frequent triggering (30-second silent monitoring period) have been established. Effective strategy parameter combinations are stored in the strategy effective library and are given priority in similar scenarios, enabling the system to have continuous adaptive evolution capabilities.

[0052] 4. This solution can achieve real-time calculation and hierarchical visualization warning of MSDV-20 based only on the vehicle's standard six-axis IMU and in-vehicle central control display. Audio-induced intervention utilizes the existing in-vehicle audio system. Suspension damping adjustment is only activated as an enhancement function when the vehicle is equipped with semi-active suspension. Non-semi-active suspension models can still independently achieve all the core functions of monitoring, warning and audio intervention. It has a very low mass production threshold and wide application compatibility in terms of hardware deployment.

[0053] In addition, the present invention provides a vehicle suspension adaptive adjustment system based on motion sickness dose values, for implementing the vehicle suspension adaptive adjustment method based on motion sickness dose values ​​as described above, comprising:

[0054] The signal acquisition module is used to acquire three-axis acceleration signals in real time during vehicle operation via an onboard six-axis IMU.

[0055] Frequency weighting module, used in accordance with ISO2631-1-1997 standard The frequency-weighted transfer function performs digital filtering and weighting on the acceleration signal, and outputs a frequency-weighted acceleration time history signal.

[0056] The sliding window integration module is used to slide in the time domain with a fixed time window width, perform discrete integration on the square of the frequency-weighted acceleration within the window and then take the square root, and calculate the motion sickness dose value of the sliding window in real time with a preset step size.

[0057] The level mapping and feature recognition module is used to compare the motion sickness dose value in the sliding window with a preset threshold and map it to the corresponding motion sickness risk level; at the same time, it identifies the current dominant vibration type by comparing the effective value of the triaxial IMU acceleration signal after frequency weighting filtering.

[0058] The graded visualization output module is used to generate display instructions on the vehicle display screen, including dynamic curves, color changes, emoticons, and text prompts, based on the risk level.

[0059] The graded intervention decision engine is used to determine whether the risk level is greater than or equal to the preset intervention trigger level. If so, the graded intervention mechanism is automatically triggered, and an intervention instruction package is generated based on the risk level and the dominant vibration type.

[0060] The audio intervention execution module is used to play background music with a 2.5~5Hz rhythm guide through the vehicle audio system;

[0061] The suspension damping adjustment module sends control signals to the shock absorber to perform differentiated damping adjustment according to the risk level and the dominant vibration type; it increases rebound damping when longitudinal / lateral sway is dominant and decreases rebound damping when vertical bump is dominant.

[0062] The effect evaluation and strategy iteration module is used to continuously monitor the trend of motion sickness dose value changes in the sliding window within the time window after the intervention is implemented, calculate the intervention effect score, determine the effectiveness of the strategy based on the score results, and make fine adjustments, upgrades or switches to the strategy. The effect evaluation and strategy iteration module also includes mode exit judgment logic, which is used to determine whether any corresponding exit condition is met, and to execute the corresponding exit action according to different exit conditions.

[0063] Compared with the prior art, the vehicle suspension adaptive adjustment system based on motion sickness dose value described in this invention has the same advantages as the vehicle suspension adaptive adjustment method based on motion sickness dose value described above, and will not be repeated here. Attached Figure Description

[0064] Figure 1 This is a flowchart of the method in an embodiment of the present invention;

[0065] Figure 2 This is a flowchart illustrating the risk level determination process in an embodiment of the present invention.

[0066] Figure 3 This is a visual interface diagram of the central control screen in an embodiment of the present invention;

[0067] Figure 4 This is a schematic diagram of the overall system architecture in an embodiment of the present invention. Detailed Implementation

[0068] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the following description is provided in conjunction with the accompanying drawings. Figure 1-4 This application will be described in further detail.

[0069] In one aspect, embodiments of the present invention provide a vehicle suspension adaptive adjustment method based on motion sickness dose values. The implementation environment of the present invention includes a six-axis IMU sensor, a cockpit domain controller, an in-vehicle central control display screen, an in-vehicle audio system, and an adjustable damping shock absorber. The six-axis IMU sensor is installed near the vehicle's center of gravity and collects three-axis acceleration signals during vehicle operation at a sampling frequency of 100Hz, which are transmitted to the cockpit domain controller via a CAN bus. The cockpit domain controller has a built-in memory and processor, storing the calculation and control program described in this invention. The processor loads and executes the program to complete frequency-weighted filtering, sliding window integration, risk level determination, vibration dominance type identification, and graded intervention decision-making. The in-vehicle central control display screen receives display commands sent by the cockpit domain controller via an LVDS / HDMI interface. The in-vehicle audio system receives audio intervention commands via an A2B audio bus. The shock absorber receives damping adjustment PWM control signals via a CAN-FD bus. IMU stands for Inertial Measurement Unit, which is simply an electronic module capable of sensing how an object "moves." A2B refers to Automotive Audio Bus. CAN-FD bus is an upgraded version of CAN bus, short for CAN with Flexible Data-Rate, which can be simply understood as "Variable Rate CAN". PWM refers to Pulse Width Modulation.

[0070] Reference Figure 1 The vehicle suspension adaptive adjustment method based on motion sickness dose values ​​includes the following steps:

[0071] S100: Real-time acquisition of three-axis acceleration signals during vehicle operation via an onboard six-axis IMU at a preset sampling frequency.

[0072] The raw acceleration signals in the X, Y, and Z directions during vehicle movement are continuously acquired by a six-axis IMU sensor at a sampling frequency of 100Hz. The raw acceleration data is input to the cockpit domain controller via the CAN bus. After receiving the data, the domain controller stores it in the raw acceleration circular queue in its memory for subsequent steps to read.

[0073] S200: As specified in ISO 2631-1-1997 standard The frequency-weighted transfer function performs digital filtering and weighting on the acquired acceleration signal to obtain the frequency-weighted acceleration time history signal.

[0074] The cockpit domain controller is defined according to ISO 2631-1-1997. The frequency-weighted transfer function performs digital filtering and weighting on the original acceleration signal. The frequency-weighted transfer function consists of four interconnected stages: a band-limited high-pass filter, an acceleration-velocity conversion stage, a previous step stage, and a band-limited low-pass filter. Filtering is performed on each of the original acceleration paths to obtain the frequency-weighted acceleration time-history signal. The data is stored in a weighted acceleration circular queue, corresponding to the data of the most recent 20 seconds.

[0075] S300: With the current time as the endpoint and a preset width W, a sliding time window is used to perform discrete integration on the square of the frequency-weighted acceleration within the window and then take the square root. The motion sickness dose value MSDV-W of the sliding window is calculated in real time with a preset step size.

[0076] The preset width W = 20 seconds and the preset step size is 1 second. The cockpit domain controller slides in the time domain with a fixed time window width W = 20 seconds, performs discrete integration on the square of the frequency-weighted acceleration within the window, and then takes the square root, calculating the MSDV-20 value in real time with a step size of 1 second.

[0077] This invention improves upon the original motion sickness dose (MSDV) formula defined in ISO 2631-1-1997. The original ISO formula for MSDV defines the global cumulative dose as follows:

[0078]

[0079] This formula is the total accumulation from the start of the journey (0) to the current time (T), which increases monotonically with the travel time and cannot represent the current short-term risk.

[0080] Therefore, this invention replaces the fixed upper limit of integration with a sliding time window of W=20 seconds, ending at the current time t. The continuous form of the 20-second sliding window motion sickness dose value (MSDV-20) is defined as follows:

[0081]

[0082] in, For the current moment, For integration variables, The signal is a frequency-weighted acceleration time history signal with an integration interval of [t-20, t], which is the time period of the most recent 20 seconds.

[0083] In an actual vehicle-mounted digital processing system, the above formula is discretized as:

[0084]

[0085] where, = 0.01 seconds (corresponding to a 100 Hz sampling interval); = 2000, which is the total number of sampling points within a 20-second window; is the frequency-weighted acceleration value at the th sampling instant; is the th sampling instant within the window, is the current output instant. The system takes 1 second as the sliding step, calculates the data of the latest 20 seconds each time to perform square summation, multiplies by the sampling interval, and then takes the square root to obtain the MSDV-20 at the current instant.

[0086] referring to Figure 1 and Figure 2 , S400: comparing MSDV-W with a plurality of preset increasing thresholds to determine the current risk level; risk level mapping and vibration feature identification.

[0087] determining whether the risk level is greater than or equal to a preset intervention trigger level, if yes, selecting and executing an intervention measure from a preset multi-modal intervention strategy matrix according to the risk level and the current dominant vibration type; if no, maintaining the current state and continuing the monitoring.

[0088] The cockpit domain controller compares the MSDV-20 calculated in step S300 with five preset increasing thresholds TH1, TH2, TH3, TH4 and TH5 to determine the current risk level L:

[0089] If MSDV-20(t)<TH1, it is determined as level 0, the stimulus amount inducing carsickness is extremely low, the passenger is in a safe and comfortable range, and no intervention is required;

[0090] If TH1≤MSDV-20(t)<TH2, it is determined as level 1, the stimulus amount is at a low level, there is a very slight induction risk, which can usually be offset by psychological adaptation, and no intervention is required;

[0091] If TH2≤MSDV-20(t)<TH3, it is determined as level 2, the stimulus amount reaches a medium level, and it is estimated that perceivable discomfort may be caused in the typical population, and the system can issue a mild warning;

[0092] If TH3≤MSDV-20(t)<TH4, it is determined as level 3, the stimulus amount is at a high level, it is estimated that the probability of inducing carsickness is relatively high, and the system should issue a moderate warning and suggest reducing the vehicle speed;

[0093] If TH4≤MSDV-20(t)<TH5, it is determined as level 4, the stimulation amount reaches the high-intensity threshold, which is predicted to produce strong motion sickness stimulation in the vast majority of the population, and the system shall trigger a high-level alert and prompt immediate deceleration or parking.

[0094] The preset intervention trigger level is level 2, and TH1 to TH5 are preset increasing thresholds, the specific values of which shall be calibrated on a real vehicle in combination with factors such as the installation position of the vehicle IMU and suspension characteristics.

[0095] At the same time, by comparing the effective values of the triaxial IMU acceleration signals after frequency-weighted filtering, the dominant type of current vibration is identified:

[0096] The vibration dominant types include longitudinal sway dominance, lateral sway dominance, vertical bump dominance, and composite type.

[0097] Longitudinal sway dominance: the effective value of longitudinal weighted acceleration is significantly higher than that of other axes, corresponding to frequent acceleration and deceleration conditions;

[0098] Lateral sway dominance: the effective value of lateral weighted acceleration is significantly higher than that of other axes, corresponding to continuous curve or frequent lane change conditions;

[0099] Vertical bump dominance: the effective value of vertical weighted acceleration is significantly higher than that of other axes, corresponding to uneven road surface or bump conditions;

[0100] Composite type: multiple axes are at a relatively high level, and no single axis is significantly dominant.

[0101] Refer to Figures 1 to 3 , S500: Graded visual output, generating corresponding display instructions according to the risk level, and displaying the current motion sickness risk state in real time on the vehicle central control display screen in the forms of dynamic curves, color changes, expression icons and text prompts.

[0102] The cockpit domain controller generates display instructions according to the risk level L and the MSDV-20 value, and sends the display instructions to the vehicle central control display screen through the LVDS / HDMI interface. The interface of the central control screen is divided into three areas:

[0103] Real-time motion sickness risk status area: displaying the real-time reading of MSDV-20, and simultaneously displaying the expression icon and text prompt corresponding to the current risk level;

[0104] MSDV curve area: drawing a dynamic curve of MSDV-20(t) changing with time, the horizontal axis shows the time history of the past 2 minutes, the vertical axis shows the MSDV value, and the color of the curve changes with the rise of the risk level (gradually changing from green to red); 5 horizontal dashed lines are drawn in the figure, corresponding to the thresholds TH1 to TH5 respectively, to intuitively reflect the risk interval where MSDV-20 is located;

[0105] Driving behavior feedback area: Outputs text driving suggestions based on the MSDV-20's status;

[0106] When longitudinal sway is dominant, and the system detects that frequent acceleration and deceleration lead to an increase in the effective value of longitudinal weighted acceleration and a continuous increase in MSDV-20: at level 2 risk, the system may prompt "Frequent acceleration and deceleration detected, it is recommended to press the accelerator pedal smoothly" or "Current longitudinal sway is strong, please reduce rapid acceleration operations"; at level 3 risk, the system may prompt "Longitudinal vibration continues to accumulate, the risk of motion sickness for rear passengers increases, it is recommended to press the brake pedal gently" or "Frequent sudden braking, please anticipate road conditions in advance and decelerate smoothly"; at level 4 risk, the system may prompt "Longitudinal stimulation has reached a high intensity, please immediately decelerate to a safe speed";

[0107] When lateral sway is dominant, and the system detects that continuous curves or frequent lane changes cause an increase in the effective value of lateral weighted acceleration: at level 2 risk, it may prompt "Frequent lane changes detected, it is recommended to reduce unnecessary lane changes" or "The lateral sway is strong, please slow down in advance before entering the curve"; at level 3 risk, it may prompt "Continuous curves cause lateral vibration accumulation, it is recommended to reduce the cornering speed" or "The lateral sway continues to increase, please avoid sharp turns"; at level 4 risk, it may prompt "The lateral stimulation has reached a high intensity, it is recommended to pull over and rest";

[0108] When vertical bumps dominate, and the system detects uneven road surfaces or bumps that cause an increase in the effective value of vertical weighted acceleration: at level 2 risk, it can prompt "Road bumps detected, it is recommended to reduce vehicle speed to pass"; at level 3 risk, it can prompt "Vertical bumps continue to be transmitted to the vehicle body, please slow down"; at level 4 risk, it can prompt "Severe bumps, extremely high risk of motion sickness, it is recommended to stop or detour";

[0109] In complex situations, when multiple axles are at a high level and no single axle is significantly dominant: at level 3 risk, the warning message may be "Multi-directional vibration superposition, the risk of motion sickness is rapidly increasing, it is recommended to adjust driving style comprehensively, accelerate gently, reduce lane changes, and reduce speed"; at level 4 risk, the warning message may be "The comprehensive vibration intensity has reached the limit, please slow down and pull over immediately".

[0110] Positive feedback for smooth driving: When the MSDV-20 drops or stabilizes at a low level, the system can output positive encouragement text, such as "Smooth driving, reduced risk of motion sickness, keep it up", "Current driving style is comfortable, good passenger experience", or "Overall risk of motion sickness is low and comfort is good during this trip".

[0111] The above text suggestions can be presented in several ways: when the risk level reaches level 3 or above, the central control screen can pop up a text pop-up window with an icon, such as "High risk of motion sickness, it is recommended to slow down"; the current suggestions can be continuously scrolled in the driving behavior feedback area and dynamically updated with the MSDV-20 value; the text suggestions can also be broadcast in voice form through the car audio system to avoid distracting the driver.

[0112] The text suggestions in the driving behavior feedback area are not a fixed list, but are dynamically generated based on three dimensions: first, the absolute value of MSDV-20, which determines the urgency of the suggestion (hint, warning, or mandatory); second, the rate of change of MSDV-20, i.e., the rate of increase, which determines the timeliness of the suggestion (e.g., "rising" or "continuously accumulating"); and third, the vibration dominance type, i.e., the comparison results of effective values ​​for each axle, which determines the specific direction of the suggestion (acceleration, braking, turning, or deceleration). For example, when the effective value of longitudinal weighted acceleration is significantly higher than that of other axles and MSDV-20 continues to rise, the system automatically generates a composite suggestion such as "continuous accumulation of longitudinal sway, motion sickness risk level 3, suggest reducing rapid acceleration." This dynamic combination method can cover a variety of driving conditions without having to list all possible scenarios.

[0113] S600: When the MSDV-20 risk level is ≥2, the system automatically triggers a graded intervention mechanism. Based on the risk level and vibration dominance type, it selects and executes intervention measures from a preset multimodal intervention strategy matrix. Intervention measures include adaptive suspension damping adjustment and audio-induced intervention.

[0114] The trigger condition for audio-induced intervention is: whether the risk level is greater than or equal to level 2. If so, background music with a 2.5-5Hz rhythm is played through the vehicle's audio system; otherwise, the audio-induced intervention is not triggered. The cockpit domain controller sends an audio playback command to the vehicle's amplifier via the A2B audio bus, selecting background music with a 2.5-5Hz rhythm stored locally or streamed. Auditory stimulation in the 2.5-5Hz frequency band can effectively guide the body's breathing frequency towards this band, activate the parasympathetic nervous system, and reduce vestibular sensitivity from a neurophysiological perspective.

[0115] Taking a level 3 risk level with vertical sway dominance as an example: the system selects a track with a steady beat and plays it at a volume of 50-52dB, while simultaneously displaying a text message prompt on the central control screen. If the risk level does not decrease within 5 minutes, the system automatically switches to alternative tracks with different beat characteristics. Based on the risk level and vibration dominance type, the system adaptively adjusts the volume to 45-55dB.

[0116] The trigger conditions for adaptive suspension damping adjustment are: MSDV-20 risk level ≥ 2, and the vehicle is equipped with a semi-active suspension. Based on the dominant vibration type identified by the effective value of the IMU triaxial weighted acceleration, the cockpit domain controller performs differentiated damping adjustment according to the following rules.

[0117] Determine whether the current dominant vibration type is longitudinal sway or lateral sway. If yes, increase the rebound damping. If no, determine whether the current dominant vibration type is vertical turbulence. If yes, decrease the rebound damping. If no, determine that the current dominant vibration type is a combination type and keep the current damping state unchanged.

[0118] For example, when the risk level is 2: if the current dominant vibration type is longitudinal sway or lateral sway, increase the rebound damping by +15% to +25%; if the current dominant vibration type is vertical turbulence, decrease the rebound damping by -10% to -20%; if the current dominant vibration type is a combination, keep the current damping state unchanged.

[0119] When the risk level is 3: if the current dominant vibration type is longitudinal sway or lateral sway, significantly increase the rebound damping by +30% to +50%; if the current dominant vibration type is vertical turbulence, moderately decrease the rebound damping by -20% to -30%; if the current dominant vibration type is a combination of both, keep the current damping state unchanged.

[0120] When the risk level is 4, the system will implement a comprehensive intervention strategy regardless of the current dominant vibration type, which means simultaneously implementing three methods: audio intervention, suspension damping adjustment, and visual prompts on the central control screen.

[0121] The cockpit domain controller calculates the target damping force adjustment value based on the risk level and the dominant vibration type, and sends a PWM control signal to the vibration damper controller via the CAN-FD bus. The adjustment process is completed linearly and gradually within 0.5 to 1.5 seconds.

[0122] Taking Level 3 risk and longitudinal sway as an example: the controller sends a PWM signal with a 30% increase in duty cycle to the solenoid valve, reducing the solenoid valve opening and increasing the damping force of the shock absorber. This suppresses the recovery speed of the vehicle's pitch motion and reduces the energy accumulation of low-frequency oscillations in the 0.1~0.5Hz frequency range. The adjustment process is completed linearly and gradually within 1 second, avoiding additional shocks caused by sudden damping changes.

[0123] Taking Level 3 risk and vertical bumps as an example: the controller sends a PWM signal with a 25% reduction in duty cycle to the solenoid valve, the solenoid valve opening increases, the damping force of the shock absorber decreases, the suspension becomes "softer", absorbs the impact energy of the road surface, and reduces the peak value of the 4~8Hz bump frequency transmitted to the vehicle body.

[0124] When the risk level reaches level 3 or above, the system simultaneously executes audio intervention and suspension damping adjustment. Taking level 4 risk and complex vibration as an example: the system simultaneously triggers audio, suspension, and central control screen, namely, playing guiding music and noise reduction prompts at a volume of 55dB; increasing rebound damping by 50% for longitudinal / lateral sway components and decreasing rebound damping by 30% for vertical bump components (achieving multi-target compromise control through a continuously adjustable valve); and displaying a visual prompt "High risk of motion sickness, recommended to slow down." All three work in tandem, completing the progressive output of all intervention actions within 20-30 seconds.

[0125] Steps S600 and S500 are executed in parallel without blocking each other.

[0126] S700: Intervention effectiveness evaluation and strategy iteration.

[0127] Within a time window following the intervention (T=20~60 seconds, e.g., 40 seconds), the system continuously monitors the trend of MSDV-20 values ​​and calculates the intervention effectiveness score E. The formula for calculating the intervention effectiveness score E is:

[0128]

[0129] in, and These are the weighting coefficients. =0.75, =0.25; T is the evaluation time window, and RMS is the root mean square value of the vehicle's vertical acceleration. The root mean square value of the vehicle's vertical acceleration within the time window following the implementation of the intervention measures; The root mean square value of the vehicle's vertical acceleration within the time window prior to the implementation of the intervention.

[0130] After calculating the intervention effect score E, the corresponding strategy adjustments are implemented based on the score results.

[0131] The system determines whether E is less than a first preset threshold. If yes, the strategy is deemed effective, and the current strategy parameter combination is recorded in the effective strategy library. If no, it determines whether E is greater than a second preset threshold. If yes, the strategy is deemed invalid, and a strategy upgrade is immediately triggered, adjusting the suspension damping to the maximum or minimum usable value while displaying a deceleration suggestion on the central control screen. If no, the effect is deemed insufficient, triggering strategy fine-tuning to keep the suspension parameters unchanged. In this embodiment, the first preset threshold is preferably -15%, and the second preset threshold is 5%.

[0132] That is, if E < -15%: the strategy is deemed valid, and the current strategy parameter combination is recorded in the strategy valid library;

[0133] If -15%≤E≤5%: the effect is deemed insufficient, triggering a fine-tuning of the strategy, switching the audio track while keeping the suspension parameters unchanged; if it is still ineffective after 2 evaluation cycles, the intervention intensity is increased (damping adjustment range is increased by 10 percentage points).

[0134] If E > 5%: the strategy is deemed invalid, and a strategy upgrade is immediately triggered, adjusting the suspension damping to the maximum or minimum available value, while displaying a forced deceleration suggestion on the central control screen.

[0135] The system updates the strategy effectiveness score every 30 seconds and uploads the evaluation results to the cloud server for subsequent OTA iteration and optimization.

[0136] S800: Mode Exit.

[0137] Determine whether the risk level of MSDV-W drops to level 1 or below within a preset number of assessment cycles. If so, exit the motion sickness comfort control mode, and the damping linearly recovers to the pre-intervention value within a preset time, and enter the silent monitoring period; if not, maintain the current intervention status.

[0138] Alternatively, determine whether the MSDV-W decreases by more than a preset threshold and whether the rate of change remains within a preset range within a subsequent preset time. If so, maintain the current intervention parameters and exit after the risk is further reduced; otherwise, maintain the current intervention status.

[0139] Alternatively, determine whether the suspension damping adjustment has reached its physical limit and whether the MSDV-W continues to rise. If so, stop the suspension damping adjustment, maintain the current damping value, and trigger a speed reduction suggestion; if not, maintain the current intervention state.

[0140] Specifically, the system exits the motion sickness comfort control mode when any of the following conditions are met:

[0141] Exit Condition 1: Risk Downgrade. When the risk level of MSDV-20 drops to ≤1 within two consecutive assessment cycles (i.e., 60 seconds), the system determines that the risk of motion sickness has been substantially reduced, the control damping linearly recovers to the pre-intervention value within 3 seconds, and enters a 30-second silent monitoring period.

[0142] Exit Condition 2: Intervention is effective and stable. When the MSDV-20 decreases by more than 15% and the rate of change remains within ±5% in the following minute, the system determines that the intervention has been effective and is stabilizing. At this point, the current intervention parameters are maintained unchanged, and the system exits after the risk has further decreased.

[0143] Exit Condition 3: Reaching the Boundary. When the damping adjustment has reached the suspension's physical limit and the MSDV-20 continues to rise, the system determines that further intervention is meaningless. At this point, the suspension damping adjustment is stopped, the current damping value is maintained, and the deceleration suggestion is triggered first.

[0144] When the adjustment is discontinued, the cockpit domain controller sends a PWM signal to the damper, controlling the damping force to gradually return to the pre-intervention value linearly within 3 seconds. During the silent monitoring period (30 seconds), the system continues to monitor the MSDV-20 value but does not trigger new interventions to prevent frequent triggering from causing occupant discomfort.

[0145] Furthermore, after the vehicle is turned off, the processor of the cockpit domain controller automatically generates a trip comfort report based on the full MSDV-20 time-series data and intervention records recorded in the memory. The report includes the peak MSDV-20 value, average MSDV-20 value, duration percentage of each risk level, and statistics on the effectiveness of intervention strategies for passengers to review and for subsequent over-the-air (OTA) algorithm iterations.

[0146] Reference Figure 4 Secondly, another embodiment of the present invention provides a vehicle suspension adaptive adjustment system based on motion sickness dose values, deployed on an on-board domain controller, for implementing the vehicle suspension adaptive adjustment method based on motion sickness dose values ​​described in the first aspect above, comprising:

[0147] The signal acquisition module is used to acquire three-axis acceleration signals in real time during vehicle operation via an onboard six-axis IMU.

[0148] Frequency weighting module, used in accordance with ISO2631-1-1997 standard The frequency-weighted transfer function performs digital filtering and weighting on the acceleration signal, and outputs a frequency-weighted acceleration time history signal.

[0149] The sliding window integration module is used to slide in the time domain with a fixed time window width W=20 seconds, perform discrete integration on the square of the frequency-weighted acceleration within the window and then take the square root, and calculate the MSDV-20 value in real time with a step size of 1 second.

[0150] The level mapping and feature recognition module is used to compare the MSDV-20 value with five preset incremental thresholds from TH1 to TH5 and map them to the corresponding motion sickness risk level (0-4); at the same time, by comparing the effective value of the triaxial IMU acceleration signal after frequency weighting filtering, it identifies the current dominant vibration type.

[0151] The graded visualization output module is used to generate dynamic curves, color changes, emoticons, and text prompts on the vehicle display screen based on the risk level and MSDV value.

[0152] The graded intervention decision engine is used to determine whether the risk level of MSDV-20 is ≥2. If so, the graded intervention mechanism is automatically triggered. Based on the risk level and vibration dominance type, the optimal intervention instruction package is generated from the preset multimodal intervention strategy matrix. The instruction package includes audio intervention parameters and suspension damping adjustment parameters.

[0153] The audio intervention execution module is used to play background music with a 2.5~5Hz rhythm guide through the vehicle audio system, and adjust the volume (45~55dB) and track type according to the risk level and vibration dominance type;

[0154] The suspension damping adjustment module sends PWM control signals to the shock absorber and performs differentiated damping adjustment according to the risk level and dominant vibration type. When longitudinal / lateral sway is dominant, the rebound damping is increased (+15%~+50%), and when vertical bump is dominant, the rebound damping is decreased (-10%~-30%). When both types are combined, the current damping state remains unchanged (combined execution at level 4). The adjustment process is completed linearly and gradually within 0.5~1.5 seconds.

[0155] The effect evaluation and strategy iteration module is used to continuously monitor the change trend of MSDV-20 within the time window (T=20~60 seconds) after the intervention is implemented, calculate the intervention effect score E, determine the effectiveness of the strategy based on the score results, and make fine adjustments, upgrades or switches of the strategy; it also includes mode exit judgment logic to determine whether any of the following exit conditions are met: (1) The risk level of MSDV-20 drops to ≤1 level within two consecutive evaluation cycles (60 seconds), at which time the damping is linearly restored to the pre-intervention value within 3 seconds and enters a 30-second silent monitoring period; (2) MSDV-20 drops by more than 15% and the change rate is maintained within ±5% within the next minute, at which time the current parameters are maintained and exit is performed after the risk is further reduced; (3) The damping adjustment has reached the physical limit of the suspension and MSDV-20 continues to rise, at which time the suspension damping adjustment is stopped, the current damping value is maintained and a deceleration suggestion is triggered.

[0156] The above embodiments are merely illustrative of several implementation methods of this disclosure, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the inventive concept of this disclosure, and these modifications and improvements all fall within the protection scope of this disclosure.

Claims

1. A vehicle suspension adaptive adjustment method based on motion sickness dose values, characterized in that, comprising the steps: collecting triaxial acceleration signals during vehicle driving in real time at a preset sampling frequency via a vehicle-mounted six-axis IMU; According to the ISO 2631-1-1997 standard The frequency-weighted transfer function performs digital filtering and weighting on the acquired acceleration signal to obtain the frequency-weighted acceleration time history signal; using a sliding time window with the current moment as the end point and a preset width W, performing discrete integration on the square of the frequency-weighted acceleration within the window and then taking the square root, so as to calculate the sliding window motion sickness dose value MSDV-W in real time at a preset step size; comparing MSDV-W with a plurality of preset increasing thresholds to determine the current risk level; determining whether the risk level is greater than or equal to a preset intervention trigger level, if yes, selecting and executing an intervention measure from a preset multi-modal intervention strategy matrix according to the risk level and the current dominant vibration type; if no, maintaining the current state and continuing monitoring.

2. The vehicle suspension adaptive adjustment method based on motion sickness dose value according to claim 1, characterized in that, The preset width W is 20 seconds, and the preset step size is 1 second; The sliding window motion sickness dose value MSDV-W is calculated according to the following discretization formula: in, The sampling interval is... This represents the total number of sampling points within the window. For the first Frequency-weighted acceleration values ​​at each sampling time This represents the current output time.

3. The vehicle suspension adaptive adjustment method based on motion sickness dose value according to claim 1, characterized in that, The step of comparing MSDV-W with a plurality of preset increasing thresholds to determine the current risk level specifically comprises: comparing MSDV-W with five preset increasing thresholds TH1, TH2, TH3, TH4, TH5: if MSDV-W < TH1, determining the level as level 0; if TH1 ≤ MSDV-W < TH2, determining the level as level 1; if TH2 ≤ MSDV-W < TH3, determining the level as level 2; if TH3 ≤ MSDV-W < TH4, determining the level as level 3; if TH4 ≤ MSDV-W < TH5, determining the level as level 4; The preset intervention trigger level is level 2; The method further comprises the step of identifying the current dominant vibration type: identifying the dominant type of the current vibration by comparing the effective values of the triaxial IMU acceleration signals after frequency weighting filtering; The dominant vibration types include longitudinal sway dominance, lateral sway dominance, vertical bump dominance, and composite type.

4. The vehicle suspension adaptive adjustment method based on motion sickness dose value according to claim 1, characterized in that, After the vehicle is turned off, a trip comfort report is automatically generated according to the full-process MSDV-W time series data and intervention records stored in the memory, and the report includes the full-process MSDV-W peak value, MSDV-W mean value, the proportion of duration of each risk level, and intervention strategy effectiveness statistics.

5. The vehicle suspension adaptive adjustment method based on motion sickness dose value according to claim 1, characterized in that, The method further comprises a graded visualization output step: generating a corresponding display instruction according to the risk level, and displaying the current motion sickness risk state in real time on the vehicle-mounted central control display screen in the forms of dynamic curves, color changes, emoticon icons and text prompts; wherein, the color of the dynamic curve gradually changes from green to red as the risk level rises.

6. The vehicle suspension adaptive adjustment method based on motion sickness dose value according to claim 1, characterized in that, The intervention measures include suspension damping adjustment: determining whether the current dominant vibration type is longitudinal sway dominance or lateral sway dominance, if yes, increasing the rebound damping; if no, determining whether the current dominant vibration type is vertical bump dominance, if yes, reducing the rebound damping; if no, determining that the current dominant vibration type is composite type, and keeping the current damping state unchanged; The adjustment range for increasing the rebound damping is +15%~+50%, and the adjustment range for reducing the rebound damping is -10%~-30%; The suspension damping adjustment is executed by sending a PWM control signal to the shock absorber solenoid valve, and the adjustment process is completed in a linear gradient within 0.5~1.5 seconds.

7. The vehicle suspension adaptive adjustment method based on motion sickness dose value according to claim 6, characterized in that, The intervention measures also include audio-induced intervention: Determine whether the risk level is greater than or equal to level 2. If so, play background music with a rhythm of 2.5~5Hz through the vehicle audio system; otherwise, do not trigger audio-guided intervention.

8. The vehicle suspension adaptive adjustment method based on motion sickness dose value according to claim 1, characterized in that, It also includes steps for intervention effectiveness evaluation and strategy iteration: Within the time window following the implementation of the intervention, the changing trend of the MSDV-W value was continuously monitored, and the intervention effect score E was calculated. If E is less than the first preset threshold, the strategy is deemed effective and the current strategy parameter combination is recorded in the strategy effective library. If not, the strategy is deemed greater than the second preset threshold. If so, the strategy is deemed invalid and a strategy upgrade is immediately triggered, adjusting the suspension damping to the maximum or minimum usable value while displaying a deceleration suggestion on the central control screen. If not, the effect is deemed insufficient, triggering a strategy fine-tuning to keep the suspension parameters unchanged. The formula for calculating the intervention effect score E is: in, and Here, T is the evaluation time window, and RMS is the root mean square value of the vehicle's vertical acceleration. The root mean square value of the vehicle's vertical acceleration within the time window following the implementation of the intervention measures; The root mean square value of the vehicle's vertical acceleration within the time window prior to the implementation of the intervention; If the strategy remains ineffective after two evaluation cycles following fine-tuning, the intervention intensity will be increased, with the damping adjustment range increased by 10 percentage points.

9. The vehicle suspension adaptive adjustment method based on motion sickness dose value according to claim 1, characterized in that, It also includes mode exit steps: Determine whether the risk level of MSDV-W drops to level 1 or below within a preset number of assessment cycles. If so, exit the motion sickness comfort control mode, and the damping linearly recovers to the pre-intervention value within a preset time, and enter the silent monitoring period; if not, maintain the current intervention status. Alternatively, determine whether the MSDV-W decreases by more than a preset threshold and whether the rate of change remains within a preset range within a subsequent preset time. If so, maintain the current intervention parameters and exit after the risk is further reduced; otherwise, maintain the current intervention status. Alternatively, determine whether the suspension damping adjustment has reached its physical limit and whether the MSDV-W continues to rise. If so, stop the suspension damping adjustment, maintain the current damping value, and trigger a speed reduction suggestion; if not, maintain the current intervention state.

10. A vehicle suspension adaptive adjustment system based on motion sickness dose value, used to implement the vehicle suspension adaptive adjustment method based on motion sickness dose value according to any one of claims 1-9, characterized in that, include: The signal acquisition module is used to acquire three-axis acceleration signals in real time during vehicle operation via an onboard six-axis IMU. Frequency weighting module, used in accordance with ISO2631-1-1997 standard The frequency-weighted transfer function performs digital filtering and weighting on the acceleration signal, and outputs a frequency-weighted acceleration time history signal. The sliding window integration module is used to slide in the time domain with a fixed time window width, perform discrete integration on the square of the frequency-weighted acceleration within the window and then take the square root, and calculate the motion sickness dose value of the sliding window in real time with a preset step size. The level mapping and feature recognition module is used to compare the motion sickness dose value in the sliding window with a preset threshold and map it to the corresponding motion sickness risk level; at the same time, it identifies the current dominant vibration type by comparing the effective value of the triaxial IMU acceleration signal after frequency weighting filtering. The graded visualization output module is used to generate display instructions on the vehicle display screen, including dynamic curves, color changes, emoticons, and text prompts, based on the risk level. The graded intervention decision engine is used to determine whether the risk level is greater than or equal to the preset intervention trigger level. If so, the graded intervention mechanism is automatically triggered, and an intervention instruction package is generated based on the risk level and the dominant vibration type. The audio intervention execution module is used to play background music with a 2.5~5Hz rhythm guide through the vehicle audio system; The suspension damping adjustment module sends control signals to the shock absorber to perform differentiated damping adjustment according to the risk level and the dominant vibration type; it increases rebound damping when longitudinal / lateral sway is dominant and decreases rebound damping when vertical bump is dominant. The effect evaluation and strategy iteration module is used to continuously monitor the trend of motion sickness dose value changes in the sliding window within the time window after the intervention is implemented, calculate the intervention effect score, determine the effectiveness of the strategy based on the score results, and make fine adjustments, upgrades or switches to the strategy. The effect evaluation and strategy iteration module also includes mode exit judgment logic, which is used to determine whether any corresponding exit condition is met, and to execute the corresponding exit action according to different exit conditions.

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