DE102022202636A1 - Method for estimating the mass of occupants on seats in a motor vehicle, as well as a seat adjustment system and a motor vehicle for carrying out this method - Google Patents

Abstract

The invention relates to a method for estimating the mass of occupants on seats (12) in a motor vehicle, in particular an autonomously driving motor vehicle, as well as a seat adjustment system (10) and a motor vehicle (12) for carrying out this method, wherein at least one electric motor (32) for adjusting at least one adjustment level (20) of the occupied seat (12), and an adjusting force of a motor variable representing the at least one electric motor (32) is detected, and a force model for a balance of forces for the adjustment of the occupied seat ( 12) is taken as a basis, and a mass (30) of the occupant on the seat (12) is determined based on the force model from the detected engine size.

Description

The invention relates to a method for estimating the mass of occupants on seats in a motor vehicle, in particular an autonomously driving motor vehicle, as well as a seat adjustment system, and a motor vehicle for carrying out this method according to the preamble of the independent claims.

State of the art

With the WO 2012/013224 A1 An occupant protection system has become known in which an adjustment device of the vehicle seat is activated by a pre-crash function of the vehicle after a dangerous situation has been detected. For example, the seat inclination or the backrest inclination is adjusted in such a way that the occupant assumes a position that is optimal for the restraint systems. The occupant protection system here has a device for occupant classification, which includes, for example, weight sensors or a camera. This makes it possible to determine whether a seat is occupied or to estimate the size of the occupant. This information from the occupant classification is used to operate the occupant protection system.

Alternatively, it is also from the DE10201220864 B4 known to read the weight of an occupant from a memory in order to use it for appropriate safety systems.

The invention is intended to enable the most accurate estimation of the mass distribution of the occupants on the vehicle seats without the need for additional, special sensors.

Disclosure of the invention

The method according to the invention for estimating the mass of occupants on seats in a motor vehicle, in particular an autonomously driving motor vehicle, as well as the seat adjustment system and the motor vehicle for carrying out this method according to the preamble of the independent claims have the advantage that the measurement of the motor force of the actuators of the Seat adjustment system can be used to determine the mass distribution of the occupant on the seat. For this purpose, the motor current or the motor speed, for example, can be recorded as a motor variable in order to estimate the corresponding mass of the occupant from the acceleration of the seat components using a force balance model for the occupied seat. Such a mass estimate can be implemented purely electronically in an existing control unit without the need for additional sensors.

The measures listed in the dependent claims make advantageous developments and refinements of the invention possible. To estimate the total mass of the occupant, the height of the entire seat can be adjusted in a simple manner, with the mass preferably being assumed to be evenly distributed over the seat surface. The mass estimation method can in particular be integrated into an entry assistance function in which the vehicle is still at a standstill. No driving dynamic forces need to be taken into account for the mass estimation, which simplifies the force model and the computational effort.

To determine the adjustment force that the electric motor applies, a motor current or a motor speed can be used as a motor variable, which is already recorded in particular for position detection and/or an anti-pinch function of the seat adjustment system. The acceleration of the respective seat components can be determined from the change in the adjustment force over time, which means that the mass distribution can be estimated from the force model.

The motor size can be recorded particularly advantageously during the activation of the electric motor during a normal seat adjustment in order to obtain a constantly updated mass estimate of the occupant. This can be done the first time you adjust the seat at the start of your journey or with any normal comfort adjustment. Alternatively, to estimate the mass, at least one seat component is briefly accelerated by the control unit in order to determine the motor size for the force model.

In a preferred embodiment, the electric motor for mass estimation is always activated in a defined position of the seat component in question, in which the efficiency losses of the seat adjustment system have already been determined. This can be done, for example, in a predetermined entry position of the seat.

mit

• m_Ins = Masse des Insassen auf dem Sitz,
• m_Sitz = Masse des Sitzes,
• a(t) = zeitliche Beschleunigung des belegten Sitzes
• F_Mot (t) = zeitliche Verstellkraft des Elektromotors,
• G * cos (α) = Hangabtriebskraft einer schiefen Ebene der Fahrbahn mit dem Winkel α
• η(t) = Verlustkomponente, die dem Wirkungsgrad des Sitz-Verstellsystems entspricht.

The following balance of forces is used as a model for estimating the mass distribution: $$\left({\text{m}}_{\text{Into the}}+{\text{m}}_{\text{Seat}}\right)*\text{a}\left(\text{t}\right)={\text{F}}_{\text{Mot}}\left(\text{t}\right)-\text{G}*\text{cos}\left(\mathrm{\alpha }\right)-\mathrm{\eta }\left(\text{t}\right)$$

with

• m _Ins = mass of the occupant on the seat,
• m _seat = mass of the seat,
• a(t) = temporal acceleration of the occupied seat
• F _Mot (t) = temporal adjustment force of the electric motor,
• G * cos (α) = downhill force of an inclined plane of the road with the angle α
• η(t) = Loss component that corresponds to the efficiency of the seat adjustment system.

If the road is flat, α = 0. For example, this equation can only be used for seat height adjustment or for various seat components.

To determine η(t), for example, a calibration run of the unoccupied seat is carried out and the motor sizes of the electric motors of the relevant adjustment levels are measured. From this, factors such as friction, stiffness or gear backlash, which determine the efficiency of the adjustment system, can be taken into account in the force model.

In order to exclude the undefined conditions when overcoming static friction, the motor variables for mass estimation are preferably only recorded as soon as the seat components move with sliding friction. Accordingly, the calibration run is only started as soon as the components move under sliding friction. This can increase the accuracy of the mass estimation.

In addition to the above-mentioned balance of forces, when measuring the engine sizes while driving, the driving dynamics forces F _Dyn of the vehicle can also be taken into account, which act on the seat, for example due to longitudinal and lateral accelerations of the vehicle. These driving dynamic forces are detected particularly conveniently with sensors already present in the vehicle, in particular by means of a sensor system of a skid protection or pre-crash system using yaw rate sensors of the vehicle.

It is particularly advantageous to assume a mass distribution of the occupant's mass using several - in particular exactly three - partial masses for the force model. In this force model, for example, a first mass m ₁ can be arranged between the seat and the backrest. A second mass m ₂ may be connected to the first mass m ₁ via a first movable lever which extends along the seat surface. A third mass m ₃ may be connected to the first mass m ₁ via a second lever which extends along the backrest. This allows the load on the individual seat components to be estimated and the appropriate adjustment speed or the appropriate energy supply to the corresponding electric motors for the quick adjustment to be specified.

To estimate the different partial masses, the different adjustment levels of the seat are controlled one after the other or simultaneously in order to measure the corresponding motor variables for the mass estimation. From the knowledge of the mass distribution on the seat components, an optimal movement trajectory for the interaction of the individual adjustment levels during quick adjustment can be determined.

To solve the system of equations for the balance of forces, the temporal adjustment force F _Mot (t) of the electric motor is determined from the motor size, the loss component η(t) from the calibration run and a(t) from the speed and/or a dynamic model of the seat adjustment. Thus, the mass of the occupant on the seat m _Ins can be calculated as the only unknown in the equation system of the force model using a recursive estimation algorithm.

The results of the mass estimation can be used in a pre-crash function, whereby the occupants can be moved into an ideal safety position for the function of the restraint systems, such as airbags or belt tensioners, using an optimal trajectory of the adjustment levels. The driver can also be brought into an upright position so that he can take control of the vehicle again during autonomous driving. Precise knowledge of the mass distribution means that unnecessarily rapid adjustment of the individual seat components can be avoided in order to protect the occupants from excessive acceleration loads. The maximum remaining adjustment time up to a possible crash event can be utilized as completely as possible.

The maximum remaining adjustment time until the predicted crash can be determined using existing pre-crash sensors. For this maximum adjustment time, the optimal trajectory can be determined based on the force model, in particular taking into account the changing mass distribution of the occupant and the updated forces acting on the vehicle. In particular, the estimate of the mass distribution can be adjusted continuously or cyclically during the quick adjustment process in order to correct the course of the optimal trajectory and/or the maximum remaining adjustment time if necessary. By dynamically adapting the force model, current changes in the driving situation and occupant characteristics can be taken into account virtually in real time in order to replan the optimal trajectory. To To estimate the mass distribution of the occupant, the dynamic multi-body model can preferably be solved in the Lagrangian formulation, whereby the inertia matrix, the Coriolis and centrifugal force matrix and the matrix of the gravitational force, the frictional force and the externally acting forces are taken into account according to the balance of forces. The actual mass distribution can also be obtained using other sensors, such as optical sensors or pressure sensors or seat occupancy sensors.

However, the method for estimating the mass of occupants on seats can also be carried out without additional hardware effort in an electric motor-adjustable seat adjustment system of a motor vehicle, with at least one control unit adjusting at least one seat component of the vehicle seat along an adjustment plane. A microcontroller is arranged in the control unit, in which the estimation algorithm for mass estimation is implemented, which determines the mass distribution from the engine variables taking into account the model of the force balance.

The motor vehicle can in particular be an autonomously driving motor vehicle that is equipped with adjustable seat components for the vehicle seat. For example, an occupant can be moved very quickly from a lying position during autonomous driving to a “self-driving” sitting position without exposing the occupants to unnecessarily high accelerations. Sensors for detecting longitudinal and lateral accelerations are preferably also arranged in the vehicle, the signals of which are fed to the force model for the method for estimating the mass of occupants on the seats. Such sensors are preferably part of an existing pre-crash sensor system.

If an electric motor drive unit is used as the actuator for adjusting the seat components, a control unit can already be integrated into it, which receives the corresponding control commands from the control unit. On the other hand, several electromotive drive units of a seat or several seats can also be controlled by a central control device, whereby the number of electronic components in the drive units can be reduced. Such a central control device can also advantageously receive signals from a pre-crash sensor system, whereby the seats can be quickly brought into an optimal position for safety-relevant restraints in the event of an impending accident. In particular, an interior monitoring system can also be arranged in the vehicle, which can also monitor the occupancy of the individual seats. For example, an interior camera or a sensitive seat occupancy mat is used for such a seat occupancy sensor system. Pressure sensors or weight sensors can also be used alternatively or additionally to detect seat occupancy. Alternatively, these sensors can also be used to determine the mass distribution of the occupants on the seat.

The invention is explained in more detail below using examples, but is not limited to this.

• 1 eine schematische Darstellung des erfindungsgemäßen Kräftegleichgewicht-Modells zur Massenabschätzung von Insassen auf KFZ- Sitzen.

Show it

• 1 a schematic representation of the force balance model according to the invention for estimating the mass of occupants on vehicle seats.

mit den Größen:

• m_Ins = Gesamtmasse des Insassen auf dem Sitz,
• m_Sitz = Masse des Sitzes,
• a(t) = zeitliche Beschleunigung des belegten Sitzes,
• F_Mot (t) = zeitliche Verstellkraft des Elektromotors,
• G * cos (α) = Hangabtriebskraft einer schiefen Ebene der Fahrbahn mit dem Neigungswinkel α
• η(t) = Verlustkomponente, die vom Wirkungsgrad des Sitz-Verstellsystems abhängt,
• F_Dyn = fahrdynamische, auf das Fahrzeug und/oder den Sitz einwirkende Kräfte.

In 1 A method for estimating the mass of occupants in a seat 12 in a motor vehicle (11) is shown schematically. The seat 12 of a seat adjustment system 10 has, as seat components 13, a seat surface 14 on which the occupant sits. A backrest 16, on which a headrest 18 is arranged, is connected to the seat 14 via a joint 15. The different seat components 13 can be adjusted relative to one another using different adjustment levels 20. The entire seat 12 can be adjusted relative to the vehicle body 11 by means of a longitudinal adjustment 28. The seat 14 can be tilted about an axis of rotation 19 by means of the seat inclination 24. The backrest 16 is rotated around the joint 15 relative to the seat 14 by means of the backrest inclination 26. The entire seat 12 can be adjusted vertically relative to the vehicle body 11 by means of the seat height adjustment 22. The different adjustment levels 20 are each actuated by at least one electric motor 32. The electric motor 32 can preferably be connected to the seat components 13 via a gear unit 33 - such as a spindle gear or an eccentric gear. The electric motors 32 are controlled by means of a control unit 36, which can be designed as a central control device or can be integrated into the electric motors 32. A microcontroller 38 is arranged in the control device 36 and controls the mass estimation method. This method uses a force balance model for the forces acting on the occupied seat. For the occupant on the seat 12, a mass distribution with a total mass m _Ins is assumed, for the seat 12 itself the mass m _seat. In order to determine the mass of the seat 12 with the occupant (m _Ins + m _seat ), one or more Adjustment levels 20 are actuated by the electric motor 32, which exerts a motor force F _Mot (t) on at least one seat component 13. This motor force F _Mot (t) causes an acceleration a(t) on the occupied seat 12 or at least on a loaded seat component 13, the course of which depends on the mass m _Ins of the occupant. The weight force G is also taken into account in the balance of forces, whereby the road inclination via cos (α) can also be included in the equation of the force model. The efficiency of the adjustment drives is included in the force model via the term η(t), which includes, for example, the friction of the mechanics, the rigidity of the electric motors or gear backlash. In addition, additional external forces F _Dyn that act on the vehicle can be taken into account, such as longitudinal and lateral accelerations of the vehicle. This results in the equation as a force model: $$\left({\text{m}}_{\text{Into the}}+{\text{m}}_{\text{Seat}}\right)*\text{a}\left(\text{t}\right)={\text{F}}_{\text{Mot}}\left(\text{t}\right)=\text{G}*\text{cos}\left(\mathrm{\alpha }\right)-\mathrm{\eta }\left(\text{t}\right)-{\text{F}}_{\text{Dyn}}$$

with the sizes:

• m _Ins = total mass of the occupant on the seat,
• m _seat = mass of the seat,
• a(t) = temporal acceleration of the occupied seat,
• F _Mot (t) = temporal adjustment force of the electric motor,
• G * cos (α) = downhill force of an inclined plane of the road with the angle of inclination α
• η(t) = loss component that depends on the efficiency of the seat adjustment system,
• F _Dyn = driving dynamics forces acting on the vehicle and/or the seat.

In this model, starting from the coordinate system 70 of the seat 12, the coordinate system 90 for the weight force G and the coordinate system 80 for the driving dynamic forces 81 are also taken into account. This system of equations can be solved for m _Ins since all other quantities can be determined. m _Sit can be assumed to be known. The time course of the F _Mot (t) can be determined using a motor variable, such as the motor current or the motor speed. The acceleration a(t) can be determined from the position detection of the adjustment levels 20, in particular via the engine speed, or by means of additional acceleration sensors, and α can be detected by appropriate sensors and/or navigation data. The efficiency η(t) of the seat adjustment system 10 can be determined via a calibration run of the unoccupied seat 12. Can be detected, for example, using sensors from the anti-skid or pre-crash system. The system of equations (I) can be solved for the different measurement times t, for example, with a recursive algorithm that can be implemented in the microcontroller 38, preferably as a least squares estimator form and/or as a Kalman filter version. To calculate the total mass m _Ins , the model can be simplified so that the dynamic driving forces can be neglected when the vehicle is at a standstill. If the occupant is assumed to be approximately centered on the seat surface 14, the total mass m _Ins can be estimated by actuating the seat height adjustment 22, in particular by means of the motor sizes of only a single electric motor 32, whereby the angle of inclination α of the road surface may also be neglected.

In order to estimate a more differentiated mass distribution of the occupant, different adjustment levels 20 are controlled by means of the associated electric motors 32. The total mass m _Ins can be assumed, for example, as a 3-mass model, in which a first mass m ₁ is arranged on the seat surface 14 in the transition area to the backrest 16. A second mass m ₂ is connected to m ₁ via a first articulated lever 41, which extends along the seat surface 14. A third mass m ₃ is connected to m ₁ via a second articulated lever 42 which extends along the backrest 16. To estimate the m _{2 ,} for example, the electric motor 32 of the seat inclination 24 is controlled. To estimate the m _{3 ,} for example, the electric motor 32 of the backrest inclination 26 is controlled. The different adjustment levels 20 can be controlled either one after the other or at the same time and the time course of the corresponding motor variables can be measured. In particular, the evaluation of the measured values can also be waited until the static friction of the adjustment levels has been overcome in order to limit the estimation process to the stationary state of the sliding friction. The motor force F _Mot (t) can be recorded in accordance with the known methods for limiting the closing force in comfort drives via a change in the speed of the electric motors 32 or directly via a motor current measurement.

Using the estimated mass distribution of the occupant on the seat 12, an occupant classification can be carried out, with which a quick adjustment of the seat components 13 can be optimized in the event of an impending crash or a safety situation for taking over the steering wheel during autonomous driving. In particular, the determined, available maximum adjustment time can be utilized in such a way that the occupant is not exposed to unnecessarily strong acceleration. on the other hand It must be ensured that the occupant is moved into an optimal seating position in time before the safety-critical event, in which the restraint systems function optimally, or the driver is ready to drive again. In this case, the adjustment movement of the different adjustment levels 20 can preferably be optimized to optimal adjustment trajectories, whereby the necessary energy requirement of the electric motors for the quick adjustment can also be optimally controlled. The estimated mass distribution can be updated continuously or cyclically using the dynamic force model. To optimize the trajectories, they can be calculated depending on the situation within the available adjustment time, or selected accordingly from a previously saved preselection. To calculate the optimal trajectory, the force model that is used to estimate the mass distribution of the occupants can also be used. The estimated mass distribution can also be used for an alternative adjustment scenario in which the time available is no longer sufficient to move the occupant into the optimal target position for a crash or for taking over the steering wheel.

It should be noted that with regard to the exemplary embodiments shown in the figures and in the description, a variety of possible combinations of the individual features with one another are possible. For example, the electric motor 32 can be designed as an EC or DC motor and combined with different gear designs 33. An electric motor 32 in combination with a spindle gear, a planetary gear or a spur gear can preferably be used as the gear drive unit. The sensor system 34 for detecting the driving dynamics forces, the angle of inclination of the road or the impending crash time can be designed by separate components, or can also be integrated into existing pre-crash or skid protection systems of the vehicle 11. To determine the acceleration of the seat components 13 to be adjusted and/or the motor power of the electric motors 32, the existing position detection and/or the anti-pinch function of the seat adjustment system 10 can be used. The control unit 36 can be an integral part of the electric drive unit 32, or can be designed as a central control device 36 for several electric drive units 32. The mass estimation method according to the invention can be used for several seats 12, in particular in an autonomously driving vehicle 11. The determined mass distribution can also be used to control other restraint systems such as belt tensioners or airbags.

QUOTES INCLUDED IN THE DESCRIPTION

This list of documents listed by the applicant was generated automatically and is included solely for the better information of the reader. The list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions.

Cited patent literature

• WO 2012013224 A1 [0002]
• DE 10201220864 B4 [0003]

Claims (16)

Method for estimating the mass of occupants on seats (12) in a motor vehicle, in particular an autonomously driving motor vehicle, wherein at least one electric motor (32) is controlled for adjusting at least one adjustment plane (20) of the occupied seat (12), and a motor variable is thereby detected , which represents an adjustment force of the at least one electric motor (32), and a force model for a force balance for the adjustment of the occupied seat (12) is used as a basis, and based on the force model from the recorded motor size, a mass (30) of the occupant on the seat (12) is determined. Procedure according to Claim 1 , characterized in that the height of the seat is adjusted as an adjustment plane (20) - in particular a backrest inclination (26) being aligned approximately vertically - this seat adjustment is preferably provided as a sequence of an entry aid function. Method according to one of the preceding claims, characterized in that a motor current or a motor speed is recorded as the motor variable, which are also used in particular for position detection and/or an anti-pinch function of the seat adjustment system (10). Method according to one of the preceding claims, characterized in that the control of the electric motor (32) for mass estimation is carried out once or several times or continuously during a normal comfort adjustment when the vehicle is at a standstill and/or while the vehicle is moving. Method according to one of the preceding claims, characterized in that the control of the electric motor (32) for mass estimation is carried out in a predetermined, defined position of the relevant at least one adjustment plane (20). Method according to one of the preceding claims, characterized in that the force model is the equation $$\left({\text{m}}_{\text{Into the}}+{\text{m}}_{\text{Seat}}\right)*\text{a}\left(\text{t}\right)={\text{F}}_{\text{Mot}}\left(\text{t}\right)=\text{G}*\text{cos}\left(\mathrm{\alpha }\right)-\mathrm{\eta }\left(\text{t}\right)$$

is used, with the following variables: m _Ins = mass of the occupant on the seat, m _seat = mass of the seat, a(t) = temporal acceleration of the occupied seat, F _Mot (t) = temporal adjustment force of the electric motor, G * cos (α) = downhill force of an inclined plane of the road with the angle α, η(t) = loss component that depends on the efficiency of the seat adjustment system. Method according to one of the preceding claims, characterized in that, for mass estimation, a calibration run of the unoccupied seat (12) is carried out for the motor size in order to estimate the efficiency due to friction or stiffness or gear backlash of the at least one adjustment plane (20). Method according to one of the preceding claims, characterized in that the motor size is only recorded after overcoming static friction at the start of the adjustment movement in a sliding friction mode - and in particular the calibration run is only recorded after overcoming the static friction. Method according to one of the preceding claims, characterized in that driving dynamic forces F _Dyn of the vehicle which cause longitudinal and lateral accelerations are recorded in the force model, which are detected in particular by means of a sensor system of an anti-skid system of the vehicle. Method according to one of the preceding claims, characterized in that a mass distribution of the mass (30) of the occupant by means of several partial masses (m ₁ , m ₂ , m ₃ ) on the seat (12) is assumed for the force model - in particular a first mass m ₁ is assumed between the seat (14) and the backrest (16), and a second mass m ₂ is connected to the first mass m ₁ via a first lever (41) which extends along the seat (14), and a third mass m ₃ is connected to the first mass m1 via a second lever (42), which extends along the backrest (16). Method according to one of the preceding claims, characterized in that the different partial masses (m ₁ , m ₂ , m ₃ ) are determined by controlling different adjustment levels (20) of the seat (12) for mass estimation, in particular the adjustment levels (20) being parallel can be controlled simultaneously or sequentially. Method according to one of the preceding claims, characterized in that the time course of the adjustment force F _Mot (t) of the electric motor (32) from the motor size and the loss component η(t) from the calibration run and a(t) from the speed of the seat Adjustment is determined, and the mass (30) of the occupant on the seat m _Ins by means of a recursive - in particular least squares - Estimation algorithm - is calculated from the equation of the force model. Method according to one of the preceding claims, characterized in that the results of the mass estimation are used in a pre-crash function to move the occupant into an ideal safety position by means of an optimal trajectory of the adjustment planes (20), with an unnecessarily rapid adjustment of the at least one Seat component (13) should be avoided while maintaining a maximum remaining adjustment time. Method according to one of the preceding claims, characterized in that the maximum remaining adjustment time until the predicted crash is determined by means of a sensor system (34), and the optimal trajectory is determined by means of the force model, in particular taking cyclic consideration of the dynamic mass distribution and the updated Forces acting on the vehicle. Seat adjustment system (10) for estimating the mass of occupants on seats (12) in a motor vehicle, in particular an autonomously driving motor vehicle, with a control unit (36) which controls at least one seat component (13) of the vehicle seat (12) along an adjustment plane (20). adjusted, wherein a microcontroller (38) is arranged in the control unit (36), in which an estimation algorithm for the mass estimation based on a force model is implemented. Motor vehicle - in particular an autonomously driving motor vehicle - with vehicle seats (12) having adjustable seat components (13), which can be adjusted by means of the seat adjustment system (10). Claim 15 and according to the procedure Claim 1 - 14 are adjustable in order to estimate the mass of occupants on the seats (12), sensors (34) being arranged in the vehicle for detecting longitudinal and lateral accelerations.

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