A vehicle sliding energy recovery method, device, equipment and storage medium

Abstract

This application provides a method, apparatus, device, and storage medium for recovering vehicle coasting energy, comprising: extracting a weighted acceleration of a preset frequency band from the longitudinal acceleration of the target vehicle when the target vehicle enters a coasting condition; integrating the weighted acceleration according to a preset time interval to obtain the motion sickness dose at the current moment; constructing a quadratic cost function based on the vehicle speed and the state of charge (SOC) of the target vehicle battery; obtaining the target recovery torque at the current moment based on the quadratic cost function and the motion sickness dose at the current moment under a set of constraints; and controlling the motor to execute according to the target recovery torque to recover the coasting energy of the target vehicle. The technical solution provided in this application achieves a dynamic balance between energy recovery efficiency, passenger comfort, and driving safety.

Description

Technical Field

[0001] This application relates to the field of vehicle technology, and in particular to a method, apparatus, device, and storage medium for recovering vehicle coasting energy. Background Technology

[0002] Currently, the anti-motion sickness and coasting energy recovery control strategies widely adopted in the industry are typically based on statically calibrated MAP maps or preset torque control models that reflect vehicle operating conditions (such as vehicle speed, accelerator pedal release rate, and brake pedal status). When a coasting intention is detected, the target recovery torque is obtained by looking up a table from the pre-calibrated MAP map. A fixed torque change rate limit or a low-pass filter is used to smooth the torque build-up process, aiming to reduce longitudinal impact. In handling external safety scenarios such as following other vehicles, the system typically monitors the distance to the vehicle in real time using a forward distance sensor. Once the distance reaches a set safety threshold, the system exits the coasting control mode and directly applies high deceleration or triggers mechanical braking.

[0003] However, the control strategy is isolated from the chassis power domain and lacks awareness of the actual state of the occupants in the cabin. The discomfort caused by coasting stems not only from transient acceleration changes but also from the cumulative effect of low-frequency longitudinal oscillations in the human vestibular system. Fixed filter parameters cannot detect or distinguish whether the occupant is in a highly sensitive state such as reading or looking at a mobile phone, or a low-sensitive state such as resting with eyes closed or looking straight ahead. This results in static torque constraints being too conservative when the occupant is not prone to motion sickness, losing recoverable kinetic energy; and not smooth enough when the occupant is highly sensitive, failing to effectively suppress motion sickness. At the same time, reactive safety interventions based on a single distance threshold lack the ability to predict the trajectory of the vehicle in front. When triggered, they drastically change deceleration, disrupting coasting consistency and causing a strong reverse physical impact, which in turn becomes the source of occupant dizziness. Summary of the Invention

[0004] In view of this, embodiments of this application provide a method, apparatus, device, and storage medium for recovering vehicle coasting energy, achieving a dynamic balance between energy recovery efficiency, passenger comfort, and driving safety.

[0005] This application mainly includes the following aspects: In a first aspect, embodiments of this application provide a method for recovering energy from vehicle coasting, the recovery method comprising: When the target vehicle enters the coasting condition, the weighted acceleration of the preset frequency band is extracted from the longitudinal acceleration of the target vehicle; The weighted acceleration is integrated over a preset time interval to obtain the motion sickness dose at the current moment; Based on the target vehicle's speed and the target vehicle's battery SOC, construct a quadratic cost function; Under the constraint set, the target recovery torque at the current moment is obtained based on the quadratic cost function and the motion sickness dose at the current moment; The control motor operates according to the target recovery torque to recover the coasting energy of the target vehicle.

[0006] Furthermore, the step of extracting weighted acceleration of a preset frequency band from the longitudinal acceleration of the target vehicle includes: The original longitudinal acceleration of the target vehicle is filtered, and the filtered original longitudinal acceleration is determined as the longitudinal acceleration of the target vehicle. Construct a frequency-weighted transfer function for longitudinal motion sickness; The longitudinal motion sickness frequency weighting transfer function is discretized into a discrete transfer function using the bilinear transform method; Based on the discrete transfer function and its filter coefficients, the weighted acceleration at the current moment is obtained through the difference equation.

[0007] Furthermore, the preset time interval is the cumulative interval from the start of this gliding to the current time, or it is a time interval with the current time as the upper limit and the duration as a preset period.

[0008] Furthermore, the construction of a quadratic cost function based on the target vehicle's speed and the target vehicle's battery SOC includes: The nominal recovery torque of the target vehicle is determined based on the vehicle speed and the state of charge (SOC) of the target vehicle battery. A quadratic cost function is constructed based on the deviation between the target recovery torque and the nominal recovery torque of the target vehicle.

[0009] Furthermore, the constraint set includes: safety margin constraint, comfort margin constraint, motor torque boundary constraint, and torque change rate constraint.

[0010] Furthermore, the safety margin constraint is constructed in the following manner: Based on the longitudinal speed of the vehicle in front of the target vehicle, the longitudinal speed of the target vehicle, and the longitudinal braking deceleration of the target vehicle, determine the minimum safe obstacle avoidance distance between the vehicle in front and the target vehicle. Based on the longitudinal distance between the preceding vehicle and the target vehicle and the minimum safe obstacle avoidance distance, the safety margin between the preceding vehicle and the target vehicle is determined. Based on the safety margin and positive gain coefficient, the safety margin constraint of the target vehicle is determined.

[0011] Furthermore, the comfort margin constraint is constructed in the following manner: Based on the occupant's state parameters, determine the occupant's current behavioral state category; Based on the aforementioned behavioral state category, determine the upper limit of motion sickness dosage tolerance; Based on the upper limit of motion sickness dose tolerance, a comfort barrier function is constructed; Based on the aforementioned comfort barrier function and smoothing gain coefficient, a comfort margin constraint is constructed.

[0012] Secondly, embodiments of this application also provide a device for recovering vehicle coasting energy, the recovery device comprising: The extraction module is used to extract the weighted acceleration of a preset frequency band from the longitudinal acceleration of the target vehicle when the target vehicle enters the coasting condition. An integration module is used to integrate the weighted acceleration according to a preset time interval to obtain the motion sickness dose at the current moment. The module is used to construct a quadratic cost function based on the target vehicle's speed and the target vehicle's battery SOC. The torque determination module is used to obtain the target recovery torque at the current moment based on the quadratic cost function and the current motion sickness dose under the constraint set. The control module is used to control the motor to perform the target recovery torque in order to recover the coasting energy of the target vehicle.

[0013] Thirdly, embodiments of this application also provide an electronic device, including: a processor, a memory, and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor communicates with the memory through the bus, and the machine-readable instructions are executed by the processor to perform the steps of the vehicle coasting energy recovery method described in the first aspect or any possible implementation of the first aspect.

[0014] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the vehicle coasting energy recovery method described in the first aspect or any possible implementation of the first aspect.

[0015] This application provides a method, apparatus, device, and storage medium for recovering vehicle coasting energy. When a target vehicle enters a coasting state, a weighted acceleration of a preset frequency band is extracted from the longitudinal acceleration of the target vehicle; the weighted acceleration is integrated over a preset time interval to obtain the motion sickness dose at the current moment; a quadratic cost function is constructed based on the vehicle speed and the state of charge (SOC) of the target vehicle battery; under a set of constraints, the target recovery torque at the current moment is obtained based on the quadratic cost function and the motion sickness dose at the current moment; and the motor is controlled to execute according to the target recovery torque to recover the coasting energy of the target vehicle.

[0016] In this way, a dynamic balance is achieved between energy recovery efficiency, passenger comfort, and driving safety.

[0017] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A flowchart of a method for recovering vehicle coasting energy provided in an embodiment of this application is shown; Figure 2 A schematic diagram of the structure of a vehicle coasting energy recovery device provided in an embodiment of this application is shown; Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of this application is shown. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the drawings in this application are for illustrative and descriptive purposes only and are not intended to limit the scope of protection of this application. Furthermore, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of this application. It should be understood that the operations in the flowcharts may not be implemented in sequence, and steps without logical contextual relationships may be reversed or implemented simultaneously. In addition, those skilled in the art, guided by the content of this application, may add one or more other operations to the flowcharts, or remove one or more operations from the flowcharts.

[0021] Furthermore, the described embodiments are merely some, not all, of the embodiments of this application. The components of the embodiments of this application described and illustrated herein can typically be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0022] The methods, apparatus, electronic devices, or computer-readable storage media described in this application can be applied to any scenario requiring coasting energy recovery. This application does not limit specific application scenarios, and any scheme using the vehicle coasting energy recovery method and apparatus provided in this application is within the protection scope of this application.

[0023] It is worth noting that the anti-motion sickness and coasting energy recovery control strategies widely adopted in the industry are typically based on statically calibrated MAP maps or preset torque control models of vehicle operating conditions (such as vehicle speed, accelerator pedal release rate, brake pedal status, etc.). When coasting intention is detected, the target recovery torque is obtained by looking up a table from the pre-calibrated MAP map, and a fixed torque change rate limit or low-pass filter is used to smooth the torque build-up process in order to reduce longitudinal impact. When dealing with external safety scenarios such as following other vehicles, the system typically monitors the distance to the vehicle in real time based on a forward distance sensor. Once the distance to the vehicle reaches a set safety threshold, the system exits the coasting control mode and directly applies high deceleration or triggers mechanical braking.

[0024] However, the control strategy is isolated from the chassis power domain and lacks awareness of the actual state of the occupants in the cabin. Occupant discomfort caused by coasting stems not only from transient acceleration changes but also from the cumulative effect of low-frequency longitudinal oscillations in the human vestibular system. Fixed filter parameters cannot detect or distinguish whether the occupant is in a highly sensitive state such as reading or looking at a mobile phone, or a low-sensitive state such as resting with eyes closed or looking straight ahead. This results in static torque constraints being too conservative when occupants are not prone to motion sickness, losing recoverable kinetic energy; and not smooth enough when occupants are highly sensitive, failing to effectively suppress motion sickness. At the same time, reactive safety interventions based on a single distance threshold lack the ability to predict the trajectory of the vehicle in front. When triggered, they drastically change deceleration, disrupting coasting consistency and causing a strong reverse physical impact, which in turn becomes a source of vertigo for the occupants. Traditional manual bench calibration methods struggle to achieve a real-time optimal trade-off between maximizing energy recovery, minimizing motion sickness index, and dynamic safety boundaries.

[0025] To address the aforementioned issues, this application proposes a method, apparatus, device, and storage medium for recovering vehicle coasting energy, achieving a dynamic balance between energy recovery efficiency, passenger comfort, and driving safety.

[0026] To facilitate understanding of this application, the technical solutions provided in this application will be described in detail below with reference to specific embodiments.

[0027] Please see Figure 1 , Figure 1 This is a flowchart illustrating a method for recovering energy from vehicle coasting, as provided in an embodiment of this application.

[0028] like Figure 1As shown in the figure, the method for recovering vehicle coasting energy provided in this application embodiment includes the following steps: Step S101: When the target vehicle enters the coasting condition, extract the weighted acceleration of the preset frequency band from the longitudinal acceleration of the target vehicle.

[0029] In this embodiment, the determination condition for the target vehicle entering a coasting state is that the accelerator pedal opening is zero and the brake pedal opening is zero. Once the target vehicle is detected to have entered a coasting state, the cabin sensing module is activated to obtain the occupant's state parameters. The preset frequency band refers to the low-frequency oscillation band that strongly stimulates the human vestibular system, specifically the frequency range of 0.1Hz to 0.5Hz. Extracting the weighted acceleration within the preset frequency band is the basis for accurately quantifying the cumulative physiological effect of motion sickness in occupants. It should be noted that the longitudinal acceleration and velocity of the target vehicle are both positive in the direction of the target vehicle's forward movement.

[0030] Regarding step S101, as an example in specific implementation, it may include the following steps: Step S1011: Filter the original longitudinal acceleration of the target vehicle and determine the filtered original longitudinal acceleration as the longitudinal acceleration of the target vehicle.

[0031] Here, the target vehicle's current raw longitudinal acceleration is acquired in real time at high frequency through the chassis inertial measurement unit. To eliminate high-frequency electrical noise from the sensor, the raw longitudinal acceleration is passed through a first-order low-pass anti-aliasing filter to obtain the preprocessed real physical acceleration signal, i.e., the longitudinal acceleration.

[0032] Step S1012: Construct the longitudinal motion sickness frequency weighting transfer function.

[0033] Here, in order to extract the low-frequency oscillation components that strongly stimulate the human vestibular system, a frequency-weighted transfer function for longitudinal motion sickness is constructed in the frequency domain. . The relation is satisfied as follows ,in, For the Laplace transform of weighted acceleration, The Laplace transform of the longitudinal acceleration of the target vehicle. Its physical characteristics are manifested as a combination of bandpass filters: the gain is close to 1.0 in the 0.1Hz to 0.5Hz frequency band, or determined according to the amplitude-frequency characteristics of the weighted network specified in ISO 2631 standard; it attenuates the high-frequency components of vehicle bumps above 2Hz and the very low-frequency components of gentle slopes, thereby separating the dizzying characteristic components from the underlying physical acceleration signal. The weighted network structure and parameters given by ISO 2631 can be directly adopted, or an equivalent calibrable implementation can be adopted, and the source of its parameters should be fixed in the implementation.

[0034] Step S1013: The longitudinal motion sickness frequency weighted transfer function is discretized into a discrete transfer function using the bilinear transformation method.

[0035] Here, since the operation is in the discrete time domain, it is necessary to transfer the continuous longitudinal motion sickness frequency weighting function. The function is converted into a discrete transfer function H(z). This application uses the bilinear transform method for discretization, resulting in a fixed set of filter coefficients, including a feedforward coefficient sequence. (i=0,1,…,N) and feedback coefficient sequence (j=1,2,…,M). Where N is the feedforward order of the discrete transfer function and M is the feedback order of the discrete transfer function.

[0036] Step S1014: Based on the discrete transfer function and the filter coefficients of the discrete transfer function, the weighted acceleration at the current moment is obtained through the difference equation.

[0037] Here, as shown in Equation (1), the weighted acceleration is calculated in real time through the following difference equation iterative calculation.

[0038] (1), in, For the current moment's weighting acceleration, For the raw longitudinal acceleration collected at historical moments, a For the vertical acceleration of historical moments, The weighted acceleration has been calculated at historical moments. This difference equation uses current and historical input-output data to recursively derive the weighted acceleration in real time.

[0039] Step S102: Integrate the weighted acceleration according to a preset time interval to obtain the motion sickness dose at the current moment.

[0040] Here, the preset time interval is either the cumulative interval from the start of the current glide to the current moment, or a time interval with the current moment as the upper limit and a preset duration. After obtaining the weighted acceleration at the current moment, the cumulative motion sickness dose at the current moment is calculated by integration. ,in, To accumulate motion sickness dose, the preset time interval can be determined in one of the following two ways: Method 1 (accumulation from the start of gliding): The preset time interval is the cumulative interval from the start of the current gliding to the current time. That is, the lower limit of integration is the start time of the current gliding condition, and the upper limit is the current time. Method 1 reflects the cumulative motion sickness stimulus of a single gliding process. Method 2 (accumulation via a sliding time window): The preset time interval has the current time as the upper limit and the duration as a preset time period. That is, the upper limit of integration is the current time, and the lower limit of integration is the time when a fixed time window W is traced back from the current time. For example, W can be 60s or 120s. Method 2 reflects the recent continuous accumulation of motion sickness effects. In the discrete implementation, the cumulative motion sickness dose at the current time is updated using a numerical integration recursive method. Assuming the preset time interval uses Method 1, the recursive formula is: = + • Ts, where Ts is the duration of the control cycle. The control cycle (e.g., 10ms) refers to the process cycle required to complete one full execution to obtain the target recovered torque.

[0041] Step S103: Based on the target vehicle's speed and the target vehicle's battery SOC, construct a quadratic matrix equation.

[0042] The purpose of this step is to establish an optimization objective function for solving the optimal recovery torque and transform it into a standard quadratic matrix form for computation in a real-time solver. The solver is a computational program or algorithm module that finds the optimal recovery torque under given constraints.

[0043] Regarding step S103, as an example in specific implementation, it may include the following steps: Step S1031: Determine the nominal recovery torque of the target vehicle based on the vehicle speed and the SOC of the target vehicle battery.

[0044] Here, the nominal regenerative torque is the expected coasting energy recovery torque under no safety or comfort constraints, representing the optimal energy efficiency benchmark under normal operating conditions. It provides the solver with a benchmark tracking target under normal operating conditions, avoiding solution divergence or outputting zero torque that does not meet driving expectations. In this step, based on the target vehicle's speed and the target vehicle's battery SOC, the nominal regenerative torque is obtained by looking up a table using a pre-calibrated MAP chart. For example, in the common speed range of urban driving conditions, the nominal regenerative torque can be calibrated as -60 N·m.

[0045] Step S1032: Construct a quadratic cost function based on the deviation between the target recovery torque and the nominal recovery torque of the target vehicle.

[0046] Here, the quadratic cost function is constructed by including energy efficiency loss penalty and comfort exceedance penalty. The expression is shown in Equation (2).

[0047] min (2), in, The target recovery torque to be solved is... For the relaxation variables of comfort soft constraints, Positive penalty weight ( >0, for example, 200). A larger value is used to strongly suppress the breach of the comfort boundary. Let the nominal recovered torque be the objective torque. The meaning of the quadratic cost function is: under the premise of satisfying the constraint set, to make the target recovered torque as close as possible to the nominal recovered torque, while minimizing... Values ​​are maintained to ensure comfort.

[0048] Step S104: Under the constraint set, based on the quadratic matrix equation and the motion sickness dose at the current moment, obtain the recovery torque at the current moment.

[0049] Here, in each control cycle, the quadratic programming solver is invoked to solve the quadratic cost function under the condition of satisfying the constraint set, and output the optimal target recovery torque and the optimal slack variable.

[0050] In this embodiment, the constraint set includes: safety margin constraint, comfort margin constraint, motor torque boundary constraint, and torque change rate constraint. The safety margin constraint represents the absolute safety baseline under any operating condition. The construction methods for each constraint are explained below.

[0051] The construction of safety margin constraints includes the following steps: Step S11: Based on the longitudinal speed of the vehicle in front of the target vehicle, the longitudinal speed of the target vehicle, and the longitudinal braking deceleration of the target vehicle, determine the minimum safe obstacle avoidance distance between the vehicle in front and the target vehicle.

[0052] Here, the actual longitudinal distance between the target vehicle and the vehicle in front, as well as the longitudinal speed of the vehicle in front and the longitudinal speed of the target vehicle, are obtained using vehicle-mounted forward radar (such as millimeter-wave radar or lidar). The minimum safe obstacle avoidance distance can be calculated using formula (3).

[0053] (3), in, This represents the total system latency (including sensing, computation, and response processes, for example, 0.35 seconds). The current road surface adhesion coefficient ,slope The maximum longitudinal braking deceleration that the vehicle can provide under the given conditions (e.g., 3.0 m / s²). The minimum static safety distance (e.g., 5m). To minimize the safe obstacle avoidance distance, Let be the longitudinal speed of the vehicle in front. The longitudinal speed of the target vehicle.

[0054] It should be noted that when there are no vehicles ahead or the radar target is lost, the safety margin constraint can degenerate into an inactive state, that is, the longitudinal distance is assigned a preset, sufficiently large value. When the longitudinal speed of the vehicle in front cannot be reliably obtained, a conservative estimation strategy is adopted to ensure safety, such as setting the longitudinal speed of the vehicle in front to zero, or using the reliable measurement value output by the radar last time as a substitute to ensure safety.

[0055] Step S12: Based on the longitudinal distance between the preceding vehicle and the target vehicle and the minimum safe obstacle avoidance distance, determine the safety margin between the preceding vehicle and the target vehicle.

[0056] Here, the safety margin is the difference between the longitudinal distance between the vehicle in front and the target vehicle and the minimum safe obstacle avoidance distance, i.e. ,in, The longitudinal distance between the vehicle in front and the target vehicle. This refers to the safety margin between the vehicle in front and the target vehicle. When the value is greater than zero, the vehicle is in a safe area; When the speed approaches zero, the risk of collision is extremely high.

[0057] Step S13: Based on the safety margin and positive gain coefficient, determine the safety margin constraint of the target vehicle.

[0058] Here, based on the safety margin and positive gain coefficient, an inequality for the safety margin constraint is constructed, namely... ,in, For the safety margin change rate, Positive gain coefficient ( (e.g., 1.5). The physical meaning of the safety margin constraint is that when a vehicle approaches the safety boundary, the allowable rate of safety margin consumption is limited by the remaining safety margin, creating a hard constraint effect of "the closer to the boundary, the more forceful the deceleration intervention." The safety margin constraint is a hard constraint and must be satisfied first during the solution process, without introducing any slack variables.

[0059] The construction of comfort margin constraints includes the following steps: Step S21: Determine the current behavioral state category of the occupant based on the occupant's state parameters.

[0060] Here, the state parameters include: the occupant's head posture and gaze focus, etc. As an example, the cockpit perception module can be an onboard OMS camera.

[0061] In one optional implementation, the occupant's behavioral state category can be output using a binary classification method, or it can be extended to a multi-level classification according to actual needs. In this application, to facilitate engineering implementation and ensure control stability, at least one discrete state identifier mode(k) is output in each control cycle. The value of the state identifier includes two categories representing high-sensitivity and low-sensitivity states. For example, when the occupant is in a high-frequency visual task state such as reading or using a mobile phone, it is determined to be a high-sensitivity state; when the occupant is in a low-visual-load state such as resting with eyes closed or looking straight ahead, it is determined to be a low-sensitivity state. To prevent frequent jumps in the state identifier due to fluctuations in single-frame detection results, a short-time hysteresis processing can be applied to the state output, or a voting mechanism based on a sliding time window can be used to keep the state identifier stable over multiple consecutive cycles.

[0062] Step S22: Determine the upper limit of motion sickness dose tolerance based on the behavioral state category.

[0063] Here, the corresponding motion sickness dose tolerance limit is matched according to the behavioral state category. The specific mapping relationship is as follows: when mode(k) represents a high-sensitivity state, a lower upper limit of motion sickness dose tolerance is selected, i.e. (e.g., 0.35); when mode(k) represents a low-sensitivity state, a higher upper limit of motion sickness dose tolerance is selected, i.e. (For example, 0.6). Among them, and All parameters are calibrable, and their specific values ​​can be obtained through road testing. In practical applications, the above mapping relationship can be further extended to a multi-level threshold table, that is, setting corresponding tolerance upper limits for different occupant behavior categories to achieve a more refined comfort adjustment effect. To ensure control stability during threshold switching, [further details are needed]. The update can be performed using hysteresis processing or linear gradual smoothing within a preset transition time to avoid threshold abrupt changes caused by state flag jumps.

[0064] Step S23: Construct a comfort barrier function based on the upper limit of motion sickness dose tolerance.

[0065] Here, after determining the current upper limit of motion sickness dosage tolerance, the comfort control barrier function is expressed as: , among which, when A value greater than zero indicates that the occupants still have a certain comfort margin; when When the value approaches zero, it indicates that the occupants have reached the comfort tolerance boundary.

[0066] Step S24: Based on the comfort barrier function and the smoothing gain coefficient, construct the comfort margin constraint.

[0067] Here, based on the comfort barrier function and the smoothing gain coefficient, an inequality for the comfort margin constraint is constructed: ,in, For the rate of change of comfort margin. The smoothing gain factor (e.g., 0.8) determines the gentleness of the intervention when the motion sickness dose approaches the red line; The slack variable represents the degree to which the comfort boundary is allowed to be exceeded; as safety constraints tighten, the allowable deviation can be increased by... To ensure safety and feasibility.

[0068] For the construction of motor torque boundary constraints, the target recoverable torque Limited to the physical limits allowed by the motor actuator, i.e. ,in, The maximum allowable negative torque limit of the motor (T_min<0, for example) The value (120 N·m) is determined by a combination of constraints, including the allowable recharge capacity of the motor / battery, SOC, and temperature.

[0069] To construct the torque change rate constraint and prevent jerking caused by torque step jumps, the torque change amplitude between adjacent control cycles is limited. ,in, The torque executed in the previous control cycle. The maximum allowable torque variation amplitude in a single cycle ( (e.g., 15 N·m / cycle). The limit is determined by a combination of constraints, including the motor / battery's permissible recharge capacity, SOC, and temperature. This limit maintains smoothness under normal conditions and can be temporarily relaxed during safety degradation.

[0070] Step S104: Under the constraint set, based on the quadratic cost function and the motion sickness dose at the current moment, obtain the target recovery torque at the current moment.

[0071] Here, the solution for the target recovery torque and the optimal relaxation variables must be controlled by the set of constraints.

[0072] In this embodiment of the application, before solving for the target recovery torque, the target recovery torque to be solved is first combined with the relaxation variables into a one-dimensional column vector: Then, to facilitate the solver's calculation, the second-order cost function is expanded and the constant term is removed, and it is reconstructed into a standard quadratic equation as shown in formula (4).

[0073] (4), in, , is a positive definite diagonal matrix used to configure the penalty weights for energy efficiency and comfort; Let be the coefficient vector of the first-order term, used to characterize the dynamic following trend of the nominal coasting target. Through reconstruction, the original minimization problem is transformed into a standard quadratic programming problem, which can be directly handled by the solver. Subsequently, the constraint set is converted into standard inequality constraint form. During the real-time execution phase, in each control cycle, the optimal solution vector that minimizes the quadratic cost function is calculated within the feasible region of the constraint set. To reduce the computational burden of the solution process and meet the real-time requirements of the vehicle controller, the solver adopts a warm-start mechanism, that is, the optimal solution vector that converged in the previous control cycle is used as the initial value of the current cycle to reduce the number of optimization iterations. After the solver converges, the target recovery torque is extracted from the optimal solution vector.

[0074] Step S105: Control the motor to execute according to the target recovery torque to recover the coasting energy of the target vehicle.

[0075] Here, the target recovery torque is sent to the motor as the recovery torque command value for the current control cycle.

[0076] In this application, when the quadratic programming problem becomes infeasible or the solver returns a non-convergence flag due to factors such as strong safety requirements, actuator boundaries, or torque change rate constraints, the system executes a safety-first degradation strategy. An example of the degradation strategy is as follows: Strategy A: Keep the safety margin constraint unchanged, temporarily relax the upper limit of the torque change rate, and... Strategy B: If resolving is still not feasible, directly output the saturated torque and simultaneously send a braking coordination request to the braking system to supplement the braking force to ensure that the safety distance requirement is met.

[0077] This application breaks through the limitations of single-point control in the chassis power domain by introducing occupant state perception as a precondition for dynamic constraints. It utilizes a quadratic programming solver with relaxation variables to replace traditional lookup tables and first-order filtering algorithms, achieving a dynamic balance between energy recovery efficiency, occupant motion sickness prevention, and driving safety. Specifically, the beneficial effects of this application are reflected in the following three aspects: First, this application achieves differentiated control and maximization of kinetic energy recovery based on occupant state. When occupants are in a low-sensitivity state, the control boundary is automatically relaxed, making the recovered torque closer to the nominal target of optimal energy efficiency, maximizing the recovery of gliding kinetic energy. When occupants are in a high-sensitivity state, the boundary is actively tightened, outputting extremely smooth control torque, effectively suppressing motion sickness. Thus, without increasing hardware costs, dynamic decoupling and optimal coordinated control of occupant comfort and energy recovery efficiency are achieved. Second, this application abandons the single transient impact constraint, directly embedding the motion sickness dosage index, reflecting the physiological sensation of the human vestibular system, into the comfort soft constraint in the quadratic programming solver. By extracting and continuously accumulating the dizzying component of the vehicle's longitudinal acceleration within a preset frequency band in real time, and continuously monitoring and suppressing low-frequency oscillations within this band, the system effectively inhibits the cumulative effect of low-frequency longitudinal oscillations that induce motion sickness in complex coasting conditions such as frequent starts and stops or long downhill slopes, fundamentally improving passenger comfort. Third, when collision risk approaches and safety constraints tighten, the solver does not randomly cut off or directly exit the original coasting control. Instead, it automatically calculates an optimal compromise torque within the optimization framework by penalizing the relaxation variables in the cost function, which just meets the safety distance requirement while maximizing comfort. The resulting technical effect is that even in extreme intervention conditions where some comfort is sacrificed to ensure driving safety, the system can still ensure that the drive motor intervenes with the smoothest gradient braking within the current physical boundary, avoiding the violent reverse physical impact caused by the step deceleration change at the moment of safety triggering in traditional solutions, achieving an extremely smooth transition above the absolute safety baseline. In summary, this application presents a complete technical solution that constructs soft constraints for comfort based on occupant status and motion sickness dosage, hard constraints for collision avoidance safety based on transient kinematics, and solves for the optimal recovery torque under constraints using quadratic programming while supporting safety-first degradation. This solution transforms the occupant's real-time physiological tolerance into quantifiable mathematical constraints. It utilizes cabin sensing equipment to identify the occupant's susceptibility to motion sickness and dynamically determines the cumulative physiological dosage threshold. Simultaneously, it combines radar-detected transient distance to the vehicle ahead to construct a collision avoidance physical boundary. Finally, through a quadratic programming solver with relaxation variables, under the hard constraints of an absolute safety boundary, it dynamically reshapes and outputs the nominal coasting recovery torque for energy efficiency.

[0078] This application provides a method for recovering energy during vehicle coasting, which achieves a dynamic balance between energy recovery efficiency, passenger comfort, and driving safety.

[0079] Based on the same application concept, this application also provides a vehicle coasting energy recovery device corresponding to the vehicle coasting energy recovery method provided in the above embodiments. Since the principle of the device in this application is similar to the vehicle coasting energy recovery method in the above embodiments of this application, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be described again.

[0080] Please see Figure 2 , Figure 2 This is a schematic diagram of a vehicle coasting energy recovery device provided in an embodiment of this application.

[0081] like Figure 2 As shown in the figure, the vehicle coasting energy recovery device 210 provided in this application embodiment includes: The extraction module 211 is used to extract the weighted acceleration of a preset frequency band from the longitudinal acceleration of the target vehicle when the target vehicle enters the coasting condition. Integration module 212 is used to integrate the weighted acceleration according to a preset time interval to obtain the motion sickness dose at the current moment; Module 213 is used to construct a quadratic cost function based on the target vehicle's speed and the target vehicle's battery SOC. The torque determination module 214 is used to obtain the target recovery torque at the current moment based on the quadratic cost function and the motion sickness dose at the current moment under the constraint set. The control module 215 is used to control the motor to perform the target recovery torque in order to recover the coasting energy of the target vehicle.

[0082] Furthermore, the extraction module 211 is specifically used for: The original longitudinal acceleration of the target vehicle is filtered, and the filtered original longitudinal acceleration is determined as the longitudinal acceleration of the target vehicle. Construct a frequency-weighted transfer function for longitudinal motion sickness; The longitudinal motion sickness frequency weighting transfer function is discretized into a discrete transfer function using the bilinear transform method; Based on the discrete transfer function and its filter coefficients, the weighted acceleration at the current moment is obtained through the difference equation.

[0083] Furthermore, the preset time interval is the cumulative interval from the start of this gliding to the current time, or it is a time interval with the current time as the upper limit and the duration as a preset period.

[0084] Furthermore, the construction module 213 is specifically used for: The nominal recovery torque of the target vehicle is determined based on the vehicle speed and the state of charge (SOC) of the target vehicle battery. A quadratic cost function is constructed based on the deviation between the target recovery torque and the nominal recovery torque of the target vehicle.

[0085] Furthermore, the constraint set includes: safety margin constraint, comfort margin constraint, motor torque boundary constraint, and torque change rate constraint.

[0086] Furthermore, the safety margin constraint is constructed in the following manner: Based on the longitudinal speed of the vehicle in front of the target vehicle, the longitudinal speed of the target vehicle, and the longitudinal braking deceleration of the target vehicle, determine the minimum safe obstacle avoidance distance between the vehicle in front and the target vehicle. Based on the longitudinal distance between the preceding vehicle and the target vehicle and the minimum safe obstacle avoidance distance, the safety margin between the preceding vehicle and the target vehicle is determined. Based on the safety margin and positive gain coefficient, the safety margin constraint of the target vehicle is determined.

[0087] Furthermore, the comfort margin constraint is constructed in the following manner: Based on the occupant's state parameters, determine the occupant's current behavioral state category; Based on the aforementioned behavioral state category, determine the upper limit of motion sickness dosage tolerance; Based on the upper limit of motion sickness dose tolerance, a comfort barrier function is constructed; Based on the aforementioned comfort barrier function and smoothing gain coefficient, a comfort margin constraint is constructed.

[0088] This application provides a vehicle coasting energy recovery device that achieves a dynamic balance between energy recovery efficiency, passenger comfort, and driving safety.

[0089] Please see Figure 3 , Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0090] like Figure 3 As shown, the electronic device 300 includes a processor 310, a memory 320, and a bus 330.

[0091] The memory 320 stores machine-readable instructions executable by the processor 310. When the electronic device 300 is running, the processor 310 and the memory 320 communicate via the bus 330. When the machine-readable instructions are executed by the processor 310, they can perform the operations described above. Figure 1The steps of the vehicle coasting energy recovery method in the illustrated method embodiment can be found in the method embodiment for specific implementation, and will not be repeated here.

[0092] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, can perform the above-described actions. Figure 1 The steps of the vehicle coasting energy recovery method in the illustrated method embodiment can be found in the method embodiment for specific implementation, and will not be repeated here.

[0093] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems and devices described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division; in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Another point is that the displayed or discussed mutual coupling or direct coupling or communication connection may be through some communication interfaces; the indirect coupling or communication connection of devices or units may be electrical, mechanical, or other forms.

[0094] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0095] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0096] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0097] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method of recovering energy of a vehicle coasting, characterized by, The recycling method includes: When the target vehicle enters the coasting condition, the weighted acceleration of the preset frequency band is extracted from the longitudinal acceleration of the target vehicle; The weighted acceleration is integrated over a preset time interval to obtain the motion sickness dose at the current moment; Based on the target vehicle's speed and the target vehicle's battery SOC, construct a quadratic cost function; Under the constraint set, the target recovery torque at the current moment is obtained based on the quadratic cost function and the motion sickness dose at the current moment; The control motor operates according to the target recovery torque to recover the coasting energy of the target vehicle.

2. The method of claim 1, wherein, The step of extracting weighted acceleration of a preset frequency band from the longitudinal acceleration of the target vehicle includes: The original longitudinal acceleration of the target vehicle is filtered, and the filtered original longitudinal acceleration is determined as the longitudinal acceleration of the target vehicle. Construct a frequency-weighted transfer function for longitudinal motion sickness; The longitudinal motion sickness frequency weighting transfer function is discretized into a discrete transfer function using the bilinear transform method; Based on the discrete transfer function and its filter coefficients, the weighted acceleration at the current moment is obtained through the difference equation.

3. The method of claim 1, wherein, The preset time interval is the cumulative interval from the start of this slide to the current time, or it is a time interval with the current time as the upper limit and the duration as a preset period.

4. The method of claim 1, wherein, The quadratic cost function is constructed based on the target vehicle's speed and the target vehicle's battery SOC, including: The nominal recovery torque of the target vehicle is determined based on the vehicle speed and the state of charge (SOC) of the target vehicle battery. A quadratic cost function is constructed based on the deviation between the target recovery torque and the nominal recovery torque of the target vehicle.

5. The method of recovering vehicle coastdown energy according to claim 1, wherein, The constraint set includes: safety margin constraint, comfort margin constraint, motor torque boundary constraint, and torque change rate constraint.

6. The method of recovering vehicle coastdown energy according to claim 5, wherein, The safety margin constraint is constructed in the following way: Based on the longitudinal speed of the vehicle in front of the target vehicle, the longitudinal speed of the target vehicle, and the longitudinal braking deceleration of the target vehicle, determine the minimum safe obstacle avoidance distance between the vehicle in front and the target vehicle. Based on the longitudinal distance between the preceding vehicle and the target vehicle and the minimum safe obstacle avoidance distance, the safety margin between the preceding vehicle and the target vehicle is determined. Based on the safety margin and positive gain coefficient, the safety margin constraint of the target vehicle is determined.

7. The method for recovering vehicle coasting energy according to claim 5, characterized in that, The comfort margin constraint is constructed in the following way: Based on the occupant's state parameters, determine the occupant's current behavioral state category; Based on the aforementioned behavioral state category, determine the upper limit of motion sickness dosage tolerance; Based on the upper limit of motion sickness dose tolerance, a comfort barrier function is constructed; Based on the aforementioned comfort barrier function and smoothing gain coefficient, a comfort margin constraint is constructed.

8. A device for recovering energy from vehicle coasting, characterized in that, The recycling device includes: The extraction module is used to extract the weighted acceleration of a preset frequency band from the longitudinal acceleration of the target vehicle when the target vehicle enters the coasting condition. An integration module is used to integrate the weighted acceleration according to a preset time interval to obtain the motion sickness dose at the current moment. The module is used to construct a quadratic cost function based on the target vehicle's speed and the target vehicle's battery SOC. The torque determination module is used to obtain the target recovery torque at the current moment based on the quadratic cost function and the current motion sickness dose under the constraint set. The control module is used to control the motor to perform the target recovery torque in order to recover the coasting energy of the target vehicle.

9. An electronic device, comprising: include: The device includes a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus. The machine-readable instructions are executed by the processor to perform the steps of the vehicle coasting energy recovery method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, performs the steps of the vehicle coasting energy recovery method as described in any one of claims 1 to 7.

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