Disclosure of Invention
The invention aims to design and develop an electronic parking structure of an electric automobile, wherein a power unit drives a second base plate to move close to or away from a first base plate, so that the electronic parking brake is turned on and off, and the parking safety is improved.
The invention also aims to design and develop a control method of the electronic parking structure of the electric automobile, which can collect road conditions and vehicle conditions of a parking place and determine the working state of the electronic parking structure based on the BP neural network.
The electronic parking structure can also accurately control the number of rotation turns of the connecting shaft according to the road condition and the vehicle condition of a parking place when the electronic parking structure works, so that the parking of a vehicle is more stable, and the parking safety is improved.
The technical scheme provided by the invention is as follows:
an electric vehicle electronic parking structure comprising:
the bearing part is provided with a shell in a sliding way, one side of the shell is provided with calipers, and the other side of the shell is provided with a cylinder body;
the first pad plate and the second pad plate are arranged on the bearing part in a relatively sliding mode and are positioned between the caliper and the cylinder body, the first pad plate is connected with the caliper, and the second pad plate is in contact with the cylinder body;
a brake disc disposed between the first pad plate and the second pad plate;
the piston is of a cup-shaped structure and is arranged in the cylinder body, and one end of the cup-shaped bottom surface is connected with the second base plate;
and the power unit is connected with the piston and used for driving the second base plate to move close to or far away from the first base plate.
Preferably, the power unit includes:
the contact part is axially arranged in the piston, and an inner thread is arranged on the axle center of one side, far away from the piston;
and one end of the connecting shaft is provided with an external thread matched with the internal thread and is in threaded connection with the contact part. The other end can rotatably penetrate out of the cylinder body;
and the motor is arranged on the other side of the shell, and the output end of the motor is connected with the connecting shaft and is used for driving the connecting shaft to rotate so as to drive the contact part to axially move along the connecting shaft.
Preferably, the power mechanism further includes:
the oil hole is arranged on the cylinder body and communicated with a closed space formed by the cylinder body and the piston;
the hydraulic oil can flow in a closed space formed by the cylinder body and the piston through the oil hole and is used for driving the piston to drive the second base plate to move close to or far away from the first base plate;
and the hand brake is used for driving the hydraulic oil to flow in a closed space enclosed by the cylinder body and the piston.
Preferably, the first backing plate and the second backing plate are provided with rubber pads on opposite sides, and the brake disc is arranged between the rubber pads.
Preferably, the method further comprises the following steps:
the slope angle sensor is used for detecting an included angle between the parking ground pavement and the horizontal plane;
the friction coefficient sensor is used for detecting the friction coefficient of the parking ground road surface and the friction coefficient of the rubber pad;
a weight sensor for detecting a vehicle body weight;
the hydraulic sensor is used for detecting the state of the hand brake;
and the controller is connected with the toe sensor, the friction coefficient sensor, the weight sensor, the hydraulic sensor and the motor, and is used for receiving detection data of the toe sensor, the friction coefficient sensor, the weight sensor and the hydraulic sensor and controlling the motor to work.
A control method of an electronic parking structure of an electric automobile collects road conditions and vehicle conditions of a parking place and determines the working state of the electronic parking structure based on a BP neural network, and specifically comprises the following steps:
step one, according to a sampling period, measuring the road surface gradient of a parking place, the road surface friction coefficient, the friction coefficient of a rubber pad, the vehicle body weight and the hand brake state through a sensor;
step two, determining an input layer neuron vector x ═ x of the three-layer BP neural network1,x2,x3,x4,x5}; wherein x is1For parking road grade, x2Coefficient of friction for parking ground, x3Is the coefficient of friction, x, of the rubber mat4As body weight, x5The state is a hand brake state;
wherein the input layer neuron value isWhen x is5When the value is 1, the hand brake is turned on, and when the value is x5When the brake pressure is 0, the hand brake is not started;
mapping the input layer vector to a hidden layer, wherein the number of neurons of the hidden layer is m;
step four, obtaining an output layer neuron vector o ═ o1}; wherein o is1The neuron value of the output layer is the working state of the motorWhen o is1When the value is 1, the motor is in a working state, and when the value is o1When 0, the motor is in the non-operating state.
Preferably, when o1When becoming 1, the control motor makes the rotatory number of turns of connecting axle satisfy:
wherein n is the number of rotation turns of the connecting shaft,for parking ground slope, M is vehicle body weight, MAIs unit weight, D0The initial distance between the rubber pads is D, the thickness of the brake disc is D, e is the base number of a natural logarithm, zeta is the friction coefficient of a parking ground road surface, η is the friction coefficient of the rubber pads, and D is the screw pitch of the external thread at one end of the connecting shaft.
Preferably, the parking ground surface gradient is:
wherein,and theta is the included angle between the parking ground and the horizontal plane.
Preferably, the number of neurons in the hidden layer is 3.
Preferably, the excitation functions of the hidden layer and the output layer both adopt S-shaped functions fj(x)=1/(1+e-x)。
The invention has the following beneficial effects:
(1) according to the electronic parking structure of the electric automobile, which is designed and developed by the invention, the power unit drives the second base plate to move close to or far away from the first base plate, so that the electronic parking brake is turned on and off, and the parking safety is improved.
(2) The control method of the electronic parking structure of the electric automobile designed and developed by the invention can acquire road conditions and vehicle conditions of a parking place and determine the working state of the electronic parking structure based on the BP neural network. The electronic parking structure can also accurately control the number of rotation turns of the connecting shaft according to the road condition and the vehicle condition of a parking place when the electronic parking structure works, so that the parking of the vehicle is more stable, and the parking safety is improved.
Detailed Description
The present invention is further described in detail below with reference to the attached drawings so that those skilled in the art can implement the invention by referring to the description text.
As shown in fig. 1, the electronic parking structure 100 of an electric vehicle according to the present invention includes: a bearing part 110 on which a second pad plate 111 and a first pad plate 112 are mounted so as to be movable forward and backward to press a brake disk D rotating together with a wheel of a vehicle; a housing 120 slidably mounted on the carrier 110 and provided with a cylinder 123, a piston 121 mounted in the cylinder 123 to move forward and backward by hydraulic oil pressure, an oil hole 124 provided in the cylinder and communicating with a closed space enclosed by the piston 121 and the cylinder 123, and a handbrake for driving hydraulic oil to flow in the closed space enclosed by the cylinder and the piston; and a power unit 130 connected to the piston 121 and used for driving the second pad plate 111 to move closer to or away from the first pad plate 112, so as to contact with the brake disk D to realize braking.
The second pad plate 111 and the first pad plate 112 are composed of the second pad plate 111 arranged to be connected with the piston 121 and the first pad plate 112 arranged to be connected with the caliper 122 of the housing 120. The second pad plate 111 and the first pad plate 112 are mounted on the carrier part 110 fixed to the vehicle body so as to be movable forward and backward toward opposite side surfaces of the brake disk D. In addition, a rubber pad 113 is attached to one surface of each of the pad plates 111 and 112 facing the brake disk D.
The housing 120 is slidably mounted to the carrier 110. More particularly, the housing 120 includes: a cylinder 123 at the rear thereof, in which a power unit 130 is installed and a piston 121 is accommodated so as to be movable forward and backward; and a caliper 122 at a front portion thereof, which is formed to be bent downward to actuate the first pad 112. The caliper 122 and the cylinder 123 are integrally formed.
The piston 121 is provided in a cylindrical shape having a cup-shaped interior and is inserted into the cylinder 123 so as to be slidable. The piston 121 presses the second pad plate 111 toward the disc D by hydraulic oil pressure or receiving a rotational force of the brake unit 140. Therefore, when hydraulic oil pressure for braking is applied to the inside of the cylinder 123, the piston 121 advances to press the second pad plate 111 against the disc D, the housing 120 is operated in the opposite direction to the piston 121 by the reaction force, and the caliper 122 presses the first pad plate 112 against the disc D, thereby performing braking.
The power unit 130 comprises a brake unit 140 composed of a motor 141 and a reducer 142, a contact part 131 axially arranged in the piston 121, an inner thread arranged on the axial center of one side far away from the piston 121, and one end close to the piston 121 contacting with the piston 121; and a connecting shaft 135 having an external thread engaged with the internal thread at one end thereof and threadedly coupled to the contact portion 131 and having the other end rotatably penetrating through the cylinder block 123. The output end of the motor 141 is connected to the connecting shaft 135, and is used for driving the connecting shaft 135 to rotate, so as to drive the contact portion 131 to move axially along the connecting shaft 135, so as to control the movement of the piston 121.
The contact portion 131 is provided in the piston 121 in a limited rotation state and is screwed with the connecting shaft 135. The contact portion 131 includes: a head 132 disposed in contact with an inner bottom surface of the piston 121; and a coupling portion 133 extending from the head portion 132 and formed with an internal thread at an inner axial center thereof to be connected with the external thread of the connecting shaft 135. The contact portion 131 serves to move forward and backward and pressurize and release the piston 121 according to the rotation of the connecting shaft 135.
The connecting shaft 135 includes: a shaft portion 136 passing through the rear portion of the housing 120 (i.e., the cylinder 123) and rotated by receiving the rotational force of the motor 141; and a flange portion 137 extending from the shaft portion 136 in the radial direction. The shaft portion 136 is rotatably mounted on the cylinder 123 by passing through the rear side of the cylinder 123, and the other end portion thereof is provided in the piston 121. At this time, one side of the shaft portion 136 passing through the cylinder 123 is connected to an output shaft of the reducer 142 and receives the rotational force of the motor 141.
In the invention, the method also comprises the following steps: the slope angle sensor is used for detecting an included angle between the parking ground pavement and the horizontal plane; the friction coefficient sensor is used for detecting the friction coefficient of the parking ground road surface and the friction coefficient of the rubber pad; a weight sensor for detecting a vehicle body weight; the hydraulic sensor is used for detecting the state of the hand brake; and the controller is connected with the toe sensor, the friction coefficient sensor, the weight sensor, the hydraulic sensor and the motor, and is used for receiving detection data of the toe sensor, the friction coefficient sensor, the weight sensor and the hydraulic sensor and controlling the motor to work.
With the above configuration, the electronic parking structure 100 in the parking operation mode is:
1. when operated by the hand brake, the driving hydraulic oil flows in the closed space enclosed by the cylinder and the piston, and then the piston 121 is driven to thereby bring the second pad plate 111 to press against the brake disk D, the housing 120 is operated in the direction opposite to the piston 121 by the reaction force, and the caliper 122 presses the first pad plate 112 against the brake disk D, thereby performing braking.
2. It is also possible to receive power through the brake unit 140 and rotate the connection shaft 135 such that the contact portion 131 presses the piston 121. Accordingly, the piston 121 brings the second pad plate 111 and the friction pad 113 into close contact with the brake disk D, while the housing 120 is operated in a direction opposite to the piston 121 by a reaction force, and the caliper 122 presses the first pad plate 112 toward the brake disk D, thereby performing braking.
According to the electronic parking structure of the electric automobile, which is designed and developed by the invention, the power unit drives the second base plate to move close to or far away from the first base plate, so that the electronic parking brake is turned on and off, and the parking safety is improved.
The invention also provides a control method of the electronic parking structure of the electric automobile, which is used for acquiring road conditions and vehicle conditions of a parking place and determining the working state of the electronic parking structure based on the BP neural network, and specifically comprises the following steps:
step one, establishing a BP neural network model.
Fully interconnected connections are formed among neurons of each layer on the BP model, the neurons in each layer are not connected, and the output and the input of neurons in an input layer are the same, namely oi=xi. The operating characteristics of the neurons of the intermediate hidden and output layers are
opj=fj(netpj)
Where p represents the current input sample, ωjiIs the connection weight from neuron i to neuron j, opiIs the current input of neuron j, opjIs the output thereof; f. ofjIs a non-linear, slightly non-decreasing function, generally taken as a sigmoid function, i.e. fj(x)=1/(1+e-x)。
The BP network system structure adopted by the invention consists of three layers, wherein the first layer is an input layer, n nodes are provided in total, n detection signals representing the working state of the equipment are correspondingly provided, and the signal parameters are given by a data preprocessing module; the second layer is a hidden layer, and has m nodes which are determined by the training process of the network in a self-adaptive mode; the third layer is an output layer, p nodes are provided in total, and the output is determined by the response actually needed by the system.
The mathematical model of the network is:
inputting a vector: x ═ x1,x2,...,xn)T
Intermediate layer vector: y ═ y: (y1,y2,...,ym)T
Outputting a vector: o ═ o (o)1,o2,...,op)T
In the invention, the number of nodes of an input layer is n-5, the number of nodes of an output layer is p-1, and the number of nodes of a hidden layer is m-3.
The input layer 5 parameters are respectively expressed as: x is the number of1For parking road grade, x2Coefficient of friction for parking ground, x3Is the coefficient of friction, x, of the rubber mat4As body weight, x5The state is a hand brake state;
wherein the input layer neuron value isWhen x is5When the value is 1, the hand brake is turned on, and when the value is x5When the brake pressure is 0, the hand brake is not started;
output layer 1 parameters are expressed as: o1The neuron value of the output layer is the working state of the motorWhen o is1When the value is 1, the motor is in a working state, and when the value is o1When 0, the motor is in the non-operating state.
And step two, training the BP neural network.
After the BP neural network node model is established, the training of the BP neural network can be carried out. And obtaining a training sample according to historical experience data of the product, and giving a connection weight between the input node i and the hidden layer node j and a connection weight between the hidden layer node j and the output layer node k.
(1) Training method
Each subnet adopts a separate training method; when training, firstly providing a group of training samples, wherein each sample consists of an input sample and an ideal output pair, and when all actual outputs of the network are consistent with the ideal outputs of the network, the training is finished; otherwise, the ideal output of the network is consistent with the actual output by correcting the weight; the output samples for each subnet training are shown in table 1.
TABLE 1 output samples for network training
(2) Training algorithm
The BP network is trained by using a back Propagation (Backward Propagation) algorithm, and the steps can be summarized as follows:
the first step is as follows: and selecting a network with a reasonable structure, and setting initial values of all node thresholds and connection weights.
The second step is that: for each input sample, the following calculations are made:
(a) forward calculation: for j unit of l layer
In the formula,for the weighted sum of the j unit information of the l layer at the nth calculation,is the connection weight between the j cell of the l layer and the cell i of the previous layer (i.e. the l-1 layer),is the previous layer (i.e. l-1 layer, node number n)l-1) The operating signal sent by the unit i; when i is 0, orderIs the threshold of the j cell of the l layer.
If the activation function of the unit j is a sigmoid function, then
And is
If neuron j belongs to the first hidden layer (l ═ 1), then there are
If neuron j belongs to the output layer (L ═ L), then there are
And ej(n)=xj(n)-oj(n);
(b) And (3) calculating the error reversely:
for output unit
Pair hidden unit
(c) Correcting the weight value:
η is the learning rate.
The third step: inputting a new sample or a new period sample until the network converges, and randomly re-ordering the input sequence of the samples in each period during training.
The BP algorithm adopts a gradient descent method to solve the extreme value of a nonlinear function, and has the problems of local minimum, low convergence speed and the like. A more effective algorithm is a Levenberg-Marquardt optimization algorithm, which enables the network learning time to be shorter and can effectively inhibit the network from being locally minimum. The weight adjustment rate is selected as
Δω=(JTJ+μI)-1JTe
Wherein J is a Jacobian (Jacobian) matrix of error to weight differentiation, I is an input vector, e is an error vector, and the variable mu is a scalar quantity which is self-adaptive and adjusted and is used for determining whether the learning is finished according to a Newton method or a gradient method.
When the system is designed, the system model is a network which is only initialized, the weight needs to be learned and adjusted according to data samples obtained in the using process, and therefore the self-learning function of the system is designed. Under the condition of appointing learning samples and quantity, the system can carry out self-learning so as to continuously improve the network performance.
When o is1When becoming 1, the control motor makes the rotatory number of turns of connecting axle satisfy:
wherein n is the number of rotation turns of the connecting shaft,for parking ground slope, M is vehicle body weight, MAIs unit weight, D0Is the initial distance between the rubber pads, D is the thickness of the brake disc,e is the base number of a natural logarithm, zeta is the friction coefficient of a parking ground road surface, η is the friction coefficient of a rubber pad, and d is the screw pitch of an external thread at one end of the connecting shaft.
Parking ground slopeComprises the following steps:
wherein,and theta is the included angle between the parking ground and the horizontal plane.
The following further describes the control method for the electronic parking structure according to the present invention with reference to specific embodiments.
Ten groups of different vehicle conditions and road conditions are taken for testing, and the specific data is shown in table 2.
TABLE 2 test data
Serial number |
Slope toe |
Coefficient of friction of road surface |
Coefficient of friction of rubber pad |
Vehicle body weight |
State of hand brake |
1 |
1° |
1.1 |
1.3 |
2000kg |
Is not used |
2 |
2° |
1.2 |
1.4 |
2300kg |
Is not used |
3 |
3° |
1.1 |
1.5 |
2500kg |
Is not used |
4 |
4° |
1.3 |
1.5 |
2200kg |
Is not used |
5 |
5° |
1.4 |
1.5 |
2400kg |
Is not used |
6 |
6° |
0.9 |
1.4 |
2600kg |
Is not used |
7 |
7° |
1.2 |
1.3 |
2800kg |
Is not used |
8 |
8° |
1.6 |
1.5 |
2500kg |
Use of |
9 |
9° |
1.4 |
1.4 |
2400kg |
Is not used |
10 |
10° |
1.5 |
1.5 |
2500kg |
Is not used |
The specific results of the control method for the electronic parking structure provided by the invention are shown in table 3.
TABLE 3 test results
As can be seen from tables 2 and 3, the vehicle can be stably parked by controlling the control method for the electronic parking structure provided by the present invention, which is reasonable.
The control method of the electronic parking structure of the electric automobile designed and developed by the invention can acquire road conditions and vehicle conditions of a parking place and determine the working state of the electronic parking structure based on the BP neural network. The electronic parking structure can also accurately control the number of rotation turns of the connecting shaft according to the road condition and the vehicle condition of a parking place when the electronic parking structure works, so that the parking of the vehicle is more stable, and the parking safety is improved.
While embodiments of the invention have been described above, it is not limited to the applications set forth in the description and the embodiments, which are fully applicable in various fields of endeavor to which the invention pertains, and further modifications may readily be made by those skilled in the art, it being understood that the invention is not limited to the details shown and described herein without departing from the general concept defined by the appended claims and their equivalents.