Active braking state monitoring unit and system

Technical field

The present application relates to an active braking state monitoring unit and system, capable of estimating a temperature of a brake disc with high precision.

Background art

In many cases, modem vehicle braking systems need to acquire a brake disc temperature. For example, an ESP function needs to use a brake disc temperature, so as to prevent brake overheating when necessary by disabling or changing a brake control strategy. Due to the fact that a brake disc is installed in such a way as to rotate with a wheel, it is difficult to detect a temperature of the brake disc by means of a sensor.

According to the current state of the prior art, an estimation module 1 shown schematically in fig. 1 is used. The estimation module 1 collects various types of information, e.g. acquires, from sensors already present in the vehicle, a wheel braking force (e.g. a wheel-side braking hydraulic pressure or a braking current) SI, a wheel speed S2, an external temperature S3 and a disc-pad contact maintenance time S4, etc., and generates estimated brake disc temperature information D1 on the basis of a thermodynamic model reflecting an energy balance relationship between the brake and the wheel. The estimated brake disc temperature information D 1 is sent to a function module 2 in which the brake disc temperature is used.

This type of estimation module 1 might have a very high tolerance, up to 100°C, between the estimated brake disc temperature and the actual brake disc temperature; this can only meet the ASIL (Automotive Safety Integrity Level)-A standard.

In view of braking safety architecture requirements and the trend towards reducing size in the process of making devices electronic, such precision is not sufficient. Monitoring of the precise state of the braking situation requires a highly precise estimated brake disc temperature.

Content of the invention

In view of the state of the prior art, an object of the present application is to provide a braking state monitoring unit and system, wherein a brake disc temperature can be estimated with high precision.

To this end, according to a first aspect of the present application, an active braking state monitoring unit is provided, used for monitoring a state of a vehicle braking system, and comprising: a first estimation module based on a physical model, configured to estimate a temperature of a brake disc using Kalman filtering technology on the basis of a measured value of a brake pad temperature sensor; and a monitoring module, configured to monitor the state of the braking system on the basis of the measured value of the brake pad temperature sensor and the estimated brake disc temperature.

In the active braking state monitoring unit, optionally, the first estimation module comprises:

(1) a linear system, with the following defined therein:

x=Ax+Bu

y=Cx

(2) a linear model, with the following defined therein:

x=Ax+Bu

y=Cx

(3) a Kalman filter and an adder,

wherein u is an input parameter, representing a braking force;

y represents a temperature at the brake pad temperature sensor; y represents the measured value of the brake pad temperature sensor, and is used as an observer;

x represents a calculated brake disc temperature;

x represents a corrected estimated brake disc temperature;

A, B and C are correlation functions or coefficients.

In the active braking state monitoring unit, optionally, the input parameter u represents a braking hydraulic pressure of an EHB system or a braking current of an EMB system.

In the active braking state monitoring unit, optionally, an environmental factor influencing brake disc temperature is inputted as a random input parameter in the first estimation module.

The active braking state monitoring unit optionally further comprises: a second estimation module, configured to estimate the temperature of the brake disc on the basis of a thermodynamic model reflecting an energy balance relationship between a brake and a wheel; and a synthesis module, configured to generate a synthesized brake disc temperature by performing comparison and credibility assessment of the estimated brake disc temperature from the first estimation module and the estimated brake disc temperature from the second estimation module.

In the active braking state monitoring unit, optionally, the active braking state monitoring unit is configured to predict a thickness of a brake pad on the basis of a prediction model in which a wheel speed, a braking force, a brake pad use mileage and a measured value of the brake pad temperature sensor are taken into account as parameters.

The present application further provides an active braking state monitoring system, used for monitoring a state of a vehicle braking system, and comprising: a brake pad temperature sensor, configured to detect a temperature at a brake pad; and the active braking state monitoring unit described above.

The active braking state monitoring system optionally further comprises a brake pad wear sensor configured to detect a brake pad wear level, wherein a signal from the brake pad wear sensor is used to correct a predicted thickness.

In the active braking state monitoring system, optionally, when the brake pad has been worn to a degree requiring use to be discontinued and replaced by a new brake pad after experiencing a conventional operation mode, the brake pad temperature sensor and/or the brake pad wear sensor continue(s) to be used.

In the active braking state monitoring system, optionally, the brake pad temperature sensor is integrated with the brake pad wear sensor.

In the active braking state monitoring system, optionally, the brake pad wear sensor comprises a detecting part configured to detect continuous variation of brake pad thickness.

The brake pad wear sensor may be of a direct or indirect distance measurement type.

In the active braking state monitoring system, optionally, the brake pad temperature sensor and the brake pad wear sensor share the same cable with a wheel speed sensor.

According to another aspect of the present application, also provided is an active braking state monitoring unit, used for monitoring a state of a vehicle braking system, and comprising: a data acquisition module based on a physical model, configured to estimate a temperature of a brake disc and acquire a brake disc and/or brake pad wear amount; a data acquisition module based on a digital model, configured to be trained using a machine learning algorithm on the basis of application condition data, in order to predict a brake disc temperature and continuously calculate a brake disc and/or brake pad wear amount; and a synthesis module, configured to compare data acquired from the data acquisition module based on the physical model and the data acquisition module based on the digital model in order to realize internal credibility assessment and/or software fault detection.

In the active braking state monitoring unit, optionally, the synthesis module is configured to generate synthesized data, at least comprising a synthesized brake disc temperature. In the active braking state monitoring unit, optionally, the data acquisition module based on the physical model comprises the first estimation module and/or the second estimation module described above in relation to the first aspect of the present application.

The present application further provides an active braking state monitoring system, used for monitoring a state of a vehicle braking system, and comprising the active braking state monitoring unit provided in the other aspect of the present application as described above.

According to the present application, brake disc temperature can be estimated with high precision; this can meet the requirements of a higher safety level, such as the ASIL-B, C or D standard.

Description of the accompanying drawings

Through the following detailed description which makes reference to the accompanying drawings, the abovementioned and other aspects of the present application can be understood more fully; in the drawings:

Fig. 1 is a schematic block diagram of a brake disc temperature estimation module according to the prior art.

Fig. 2 is a schematic diagram of a brake pad wear sensor which may be used in the present application.

Fig. 3 is a schematic block diagram of a brake disc temperature estimation module according to an embodiment of the present application.

Fig. 4 is a schematic block diagram of an active braking state monitoring unit according to an embodiment of the present application.

Fig. 5 is a schematic block diagram of an active braking state monitoring unit according to another embodiment of the present application.

Fig. 6 is a schematic block diagram of an active braking state monitoring unit according to another embodiment of the present application. Particular embodiments

The present application relates to active braking state monitoring technology, used to monitor a state of a wheel braking system. The braking system comprises a brake disc, installed in such a way as to rotate together with a wheel, and a pair of brake pads, which are arranged on two opposite sides of the brake disc and apply a braking force to the brake disc when actuated. The braking system may be a braking system of any existing type, such as an EHB (electro-hydraulic braking) system or an EMB (electro-mechanical braking) system.

The braking state monitoring system of the present application may comprise a BPWS (brake pad wear sensor), used to detect a wear level of the brake pads.

The BPWS used here may be of a conventional type, and can output a replace wear level signal (to warn a driver to replace the brake pads), or first of all output a replace wear level signal and subsequently output a forced stop wear level signal (to warn the driver to stop driving or force the vehicle to stop).

According to a feasible embodiment of the present application, the BPWS may continuously detect and output a brake pad wear level (residual thickness), including a wear level located between two thresholds (a replace wear level and a forced stop wear level).

Specifically, according to this embodiment, the BPWS may comprise an induced magnetic field type detecting part, wherein induced magnetic fields (eddy currents) generated when the brake pads approach are different for different thicknesses, and the braking state monitoring system can thereby determine the thickness of the brake pads (i.e. determine the wear amount). Such a BPWS may be said to be of the direct distance measurement type.

Similarly, an induced magnetic field type distance sensor may be provided for the brake disc, being arranged in a fixed position facing the brake disc. As the thickness of the brake disc decreases, an induced magnetic field (eddy current) generated changes, and the sensor can therefore measure the thickness of the brake disc (i.e. determine the wear amount).

As an alternative solution, the braking state monitoring system may use signals of a WSS (wheel speed sensor), a braking force sensor and a brake pad temperature sensor (which may be a separate temperature sensor or integrated in the BPWS to form a BPWS T) to estimate the thickness of the brake pads. In this way, a brake pad thickness prediction model (a physical model) may be established, wherein compared with a brake pad thickness predicted on the basis of a linear relationship between brake pad thickness and brake pad use mileage, various factors causing the speed of brake pad thickness reduction to increase or decrease are taken into account. In this way, highly precise continuous brake pad wear monitoring is realized. Using signals from the BPWS or BPWS T, the predicted brake pad thickness may be corrected.

It will be understood that in a similar manner, the brake disc thickness may be predicted using a brake disc thickness prediction model.

As an alternative solution, the BPWS (or BPWS T) may comprise a detecting part installed in such a way as to move with the brake pads, which comes into contact with the brake disc together with the brake pads. The detecting part of the BPWS (or BPWS T) is worn together with the brake pads, so that the braking state monitoring system can determine the thickness of the brake pads on the basis of the length of the detecting part.

As an alternative solution, the BPWS may comprise a distance detecting part, which detects the distance moved by the brake pads to reach a position of contact with the brake disc, and the braking state monitoring system can determine the thickness of the brake pads on the basis of the distance moved by the brake pads. Such a BPWS may be said to be of the indirect distance measurement type.

Upon discovering that the thickness of the brake pads has reached the replace wear level, the braking state monitoring system warns the driver to replace the brake pads; the driver will then generally drive to a service station to replace the brake pads. However, if the driver or an automatic driving system ignores the warning, then after driving on for a certain mileage, if it is discovered that the thickness of the brake pads has reached the forced stop wear level, the braking state monitoring system may warn the driver to stop driving or forcibly stop the vehicle in a safe mode. In addition, if the braking system develops a fault, the braking state monitoring system may also stop the vehicle.

The BPWS (including the BPWS T) may take the form shown in fig. 2, comprising a detecting part 3a and a cable 3b. The cable 3b may be integrated in a WSS cable to form a multi-core cable, thereby lowering costs and reducing the amount of labour needed to lay the cables.

The brake pad wear level, as well as the brake pad temperature and brake disc temperature, are often used in many vehicle functions, e.g. a fault protection safety function and a fault protection operation function in an ESP, as key parameters for monitoring the braking system state. If one or more of these parameters exceeds a corresponding threshold, then a control strategy of these functions is disabled or changed.

In order to detect the brake pad temperature, the braking state monitoring system of the present application comprises a brake pad temperature sensor (as stated above, this may be integrated in the BPWS).

In the case of a non-contact sensor (not coming into contact with the brake disc), such as a brake pad temperature sensor, a BPWS and a BPWS T, once used brake pads have been replaced with new brake pads, the sensor may be used again if it is still in a good state (capable of normal operation). The sensor is only replaced with a new sensor after being destroyed/wom, e.g. if the vehicle is forced to stop in safe mode because the thickness of the brake pads has reached the forced stop wear level.

In view of the fact that the brake disc rotates with the wheel, the detection of brake disc temperature is not as easy as in the case of brake pads. According to the present application, an estimation module 10 based on Kalman filtering as shown schematically in fig. 3 is used; this is a module based on a physical model, and is capable of estimating the brake disc temperature with a higher precision than the estimation module 1 shown in fig. 1.

As shown in the figure, a Kalman filter is a feedback-type filter, and is used in a linear system which varies with time. The estimation module 10 based on Kalman filtering mainly comprises:

(1) a linear system, with the following defined therein:

x=Ax+Bu

y=Cx

(2) a linear model, with the following defined therein:

x=Ax+Bu

y=Cx

(3) a Kalman filter K and an adder å,

wherein u is an input parameter, representing a braking force (which may be a braking hydraulic pressure in EHB or a braking current in EMB);

y represents a temperature value at a brake pad temperature sensor or BPWS T;

y represents a measured value of a brake pad temperature sensor or BPWS T, and is used as an observer (observation parameter) in the estimation module 10;

x represents a calculated brake disc temperature;

x represents a (corrected) brake disc temperature estimated after taking into account a correction value Dc;

A, B and C are correlation functions/coefficients.

A, B and C may be determined by tests, experiments and/or experience.

In the estimation module 1 , u is inputted into the linear system; x and y are calculated on the basis of u in the linear system. Furthermore, u and the correction value Dc are inputted into the linear model; x and y are calculated in the linear model. The magnitudes of y and y are inputted into the adder å, and the difference therebetween is inputted into the Kalman filter K to generate the correction value Dc, which is fed back into the linear model.

By using the estimation module 10, the brake disc temperature is estimated with relatively high precision, and therefore might meet the ASIL-B standard. In other words, the tolerance of estimated brake disc temperature information D 1 is less than the tolerance of the estimation module 1 shown in fig. 1 , therefore the active braking state monitoring system may have increased precision and safety level.

The estimated brake disc temperature information D 1 might also be collected by various function modules using brake disc temperature.

Fig. 4 shows a schematic block diagram of an active braking state monitoring unit according to an embodiment of the present application, which may be included in the active braking state monitoring system. In the active braking state monitoring unit, the estimation module 10 as described above receives input information SI 0, comprising a detected brake pad temperature (y) and a parameter (u) representing the braking force, and the estimation module 10 estimates the brake disc temperature (x). Output information of the estimation module 10 comprises estimated brake disc temperature information D 1 , and is collected by a monitoring model 20. The monitoring model 20 also collects other information such as brake pad wear level and brake disc temperature, and therefore monitors the state of the braking system.

The estimation module 10 may further receive optional information Sl l as a random input parameter; examples thereof include information based on a camera/laser radar/map, such as an ambient state (ambient temperature, wet, dry and icy road states, etc.), such that cooling or heating effects of the road or ambient climate can be taken into account. The random input parameter may be inputted into the linear system of the estimation module 10, and in this case, the formula x=Ax+Bu is replaced by x=Ax+Bu+Dw, wherein w denotes the random input parameter, and D is a function or coefficient associated with the random input parameter.

According to a further embodiment of the present application, an active braking state monitoring unit as shown schematically in fig. 5 may be included in the active braking state monitoring system, and comprises the estimation module 10 described above and the estimation module 1 shown in fig. 1. Brake disc temperature information D1 estimated by the estimation module 10 (which might comply with the ASIL-B level) and brake disc temperature information D2 estimated by the estimation module 1 (which might comply with the ASIL-A level) are compared and/or undergo credibility (rationality) assessment in a synthesis module 30, to generate synthesized brake disc temperature information D3; the precision of the synthesized brake disc temperature information D3 is higher than that of the estimated brake disc temperature information D 1 , and might comply with the ASIL-C or D standard. In other words, the tolerance of the synthesized brake disc temperature information D3 is less than that of the estimated brake disc temperature information D 1.

The synthesized brake disc temperature information D3 is collected by the monitoring model 20, and the monitoring model 20 monitors the state of the braking system on the basis of the synthesized brake disc temperature information D3 and other associated information. Due to the contribution of the synthesized brake disc temperature information D3, the precision and safety level of the active braking state monitoring system can be further increased.

The synthesized brake disc temperature information D3 may also be used by other function modules using brake disc temperature.

The active braking state monitoring unit may also monitor a fault in a braking device; a fault in the braking device might result in a loss of efficiency or a loss of safety in the braking system. This kind of fault monitoring may comprise braking drag torque fault detection, braking device breakage or overheating, friction coefficient loss, etc.

It can be seen that the present application uses Kalman filtering to estimate the brake disc temperature on the basis of the detected brake pad temperature, and can thereby achieve high precision and high reproducibility of brake disc temperature estimation. Furthermore, no special temperature sensor is used to acquire the brake disc temperature, therefore the active braking state monitoring system can reduce dimensions and lower costs. Using the active braking state monitoring unit to monitor the braking system state in real time, it can be ensured that a fault protection safety function and a fault protection operation function are realized. High-level safety requirements can be met. Cables of the BPWS and brake pad temperature sensor, or a cable of the BPWS T, may be integrated with the WSS cable, with no need to use an additional connector system, therefore the active braking state monitoring system can further lower costs.

Fig. 6 shows an active braking state monitoring unit according to another embodiment of the present application, comprising a data acquisition module 100 based on a physical model, a data acquisition module 200 based on a digital model, and a synthesis module 300.

The data acquisition module 100 based on the physical model may acquire a brake disc temperature (Temp Physi) and a brake disc/brake pad wear amount (Wear Physi), wherein the brake disc/brake pad wear amount may be acquired from a sensor (possibly with correction), and the brake disc temperature may be estimated in a manner described above or in another existing manner. For example, the brake disc temperature may be estimated using Kalman filtering as described above, or estimated on the basis of wheel braking force, wheel speed, external temperature and disc-pad contact maintenance time. Thus, the estimation module 1 and/or 10 described above may be included in the data acquisition module 100 based on the physical model.

The data acquisition module 200 based on the digital model is of the machine-learning (AI) type, is trained on the basis of application condition data, uses a machine -based learning algorithm to predict a temperature of the brake disc (Temp Numer) and continuously calculates a wear amount of the brake disc/brake pad (Wear Numer).

Data (Data Physi) obtained from the data acquisition module 100 based on the physical model (on the basis of a thermodynamic model/Kalman filter) and data (Data Numer) obtained from data of the data acquisition module 200 based on the digital model are compared and verified with respect to each other in the synthesis module 300, in order to realize internal credibility (rationality) assessment and/or a software fault detection scheme. If an output signal of the data acquisition module 100 based on the physical model is too high compared with the data acquisition module 200 based on the digital model, a downgrade operation of a corresponding function and/or a warning may be implemented. The synthesis module 300 generates synthesized data of higher precision, including synthesized brake disc temperature information.

The present application also relates to an active braking state monitoring system including the active braking state monitoring unit shown in fig. 6.

Although the present application has been described here with reference to particular embodiments, the scope of the present application is not limited to the details shown. Various amendments may be made to these details without departing from the basic principles of the present application.