CN112631260A - Time lag analysis method for composite structure loop of networked motion control system of electric automobile - Google Patents

Time lag analysis method for composite structure loop of networked motion control system of electric automobile Download PDF

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CN112631260A
CN112631260A CN202110045389.1A CN202110045389A CN112631260A CN 112631260 A CN112631260 A CN 112631260A CN 202110045389 A CN202110045389 A CN 202110045389A CN 112631260 A CN112631260 A CN 112631260A
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CN112631260B (en
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曹万科
王乐成
李建威
何洪文
刘韶
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Beijing Institute of Technology BIT
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    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
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    • G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
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Abstract

The invention belongs to the field of electric automobile networked motion control technology and system, and particularly relates to a loop time-delay analysis method of a composite structure of an electric automobile networked motion control system. The invention can accurately obtain the upper bound of network induced delay in the electric automobile networked control system loop as a system loop time-lag analysis method, and provides technical method support for designing a highly reliable vehicle motion controller, ensuring vehicle motion control stability and further improving vehicle operation safety.

Description

Time lag analysis method for composite structure loop of networked motion control system of electric automobile
Technical Field
The invention belongs to the field of electric automobile networked control technology and system, and particularly relates to a time lag analysis method for a composite structure loop of an electric automobile networked motion control system.
Background
Automobile motion control is a classic topic of automobile technology development. In recent years, with the rapid development of electric vehicles, how to realize stable and efficient electric vehicle motion control becomes a focus problem of the development of the automobile industry. The traditional mechanical and hydraulic structure has the problems of large volume, slow response, difficult arrangement and the like, and can not meet the increasingly severe requirements of the motion control system of the electric automobile; on the other hand, with the development of semiconductor integration technology and industrial field bus technology, the networked motion control system of the electric automobile becomes possible due to the system on chip and the vehicle-mounted network which have excellent performance and low price.
The automobile networked motion control system uses a line control technology and a vehicle-mounted network to acquire vehicle state signals and send control commands, replaces the traditional mechanical and hydraulic transmission devices, has the characteristics of small volume, flexible arrangement, good controllability, high response speed and the like, and provides possibility for realizing accurate and rapid vehicle dynamics control.
On the other hand, the use of the on-board network will inevitably introduce signal transmission delays. The delay directly affects the real-time performance and the system stability of vehicle motion control, and further affects the vehicle operation safety, and becomes a new challenge for the development of the networked motion control technology of the electric vehicle. The existing time lag analysis methods, such as a network deduction theory and a Markov time delay model, mostly focus on time delay analysis of partial links of a system, so that the estimation of an upper time delay bound is inaccurate, and the time delay upper bound has certain limitations, and cannot meet the real-time application requirements of a networked motion control system of an electric vehicle, so that the real-time performance of a controller and the stability of the system are reduced, and further the running safety of the vehicle is influenced.
Disclosure of Invention
The invention aims to overcome the defects of the existing network time lag analysis method, provides a composite structure loop time lag analysis method of an electric automobile networked motion control system, can obtain the maximum time delay of the control loop of the electric automobile networked motion control system, and provides data support for the design of a network time lag down control algorithm, so that the real-time performance and the system stability of a controller are improved, and the running safety of an electric automobile is further improved.
The invention is realized by the following specific steps:
the time lag analysis method for the composite structure loop of the networked motion control system of the electric automobile comprises the following steps:
Figure 998348DEST_PATH_IMAGE001
analyzing related concepts and definitions in a time delay manner;
Figure 836860DEST_PATH_IMAGE002
analyzing the type of a delay system;
Figure 85439DEST_PATH_IMAGE003
and (4) loop delay envelope analysis. Wherein the steps
Figure 215069DEST_PATH_IMAGE001
The related concepts and definitions of the time delay analysis are steps
Figure 950813DEST_PATH_IMAGE002
Delayed system type identification and procedure
Figure 976538DEST_PATH_IMAGE003
The loop delay envelope analysis provides conceptual support; step (ii) of
Figure 164942DEST_PATH_IMAGE002
Utilizing the steps
Figure 832684DEST_PATH_IMAGE001
The related concepts are subjected to the statistics of the type of the delay system and are steps
Figure 970404DEST_PATH_IMAGE003
Providing a delayed envelope analysis object; step (ii) of
Figure 229347DEST_PATH_IMAGE003
Delay loop envelope utilization step
Figure 701786DEST_PATH_IMAGE001
Related concepts and steps
Figure 907639DEST_PATH_IMAGE002
And analyzing the object and deducing to obtain the mathematical expression of the upper limit of the loop delay of the system.
Step (ii) of
Figure 899866DEST_PATH_IMAGE001
The method comprises four concept definitions which are respectively a network node delay component, a control loop delay chain, a delay chain type analysis and a delay boundary envelope analysis. The network node delay component is used for describing the composite delay time of one network node; the control loop delay chain is used for describing the composite delay time of one control loop; the type analysis of the delay chain is about the description of the type classification of various control loop delay chains consisting of network nodes with different trigger modes; the delay boundary envelope analysis is to find the description of the delay upper bound of the delay chain of the control loop; the network node delay assembly consists of delay element task queuing time, task execution time, communication queuing time and communication execution time.
The network node types comprise sensor nodes, controller nodes and actuator nodes, wherein for the sensor nodes, under a time trigger mode, the delay components comprise task execution time, communication queuing time and communication execution time; in the event trigger mode, the delay assembly comprises task execution time, communication queuing time and communication execution time; for the controller node, in a time trigger mode, the delay assembly comprises task queuing time, task execution time, communication queuing time and communication execution time; in the event trigger mode, the delay assembly comprises task execution time, communication queuing time and communication execution time; for an actuator node, under a time trigger mode, a delay assembly of the actuator node comprises task queuing time and task execution time; in the event trigger mode, the delay component comprises task execution time.
The delay chain of the control loop is generally formed by connecting network node delay components through channels among nodes, wherein the network nodes comprise sensor nodes, controller nodes and actuator nodes. The inter-node path includes a forward path and a feedback path. The control loop delay chain length formula is as follows:
Figure 798552DEST_PATH_IMAGE005
wherein
Figure 758287DEST_PATH_IMAGE006
Indicating the first in the control loop
Figure 502252DEST_PATH_IMAGE008
The length of the delay element of a network node,
Figure 614564DEST_PATH_IMAGE009
indicating the number of network nodes in the control loop,
Figure 418572DEST_PATH_IMAGE010
。
step (ii) of
Figure 68865DEST_PATH_IMAGE002
The delay system type analysis process refers to the induction and classification of the delay chain of the control loop based on the node driving mode, and the number of types of the delay chain meets the following formula:
Figure 616521DEST_PATH_IMAGE011
wherein
Figure 380078DEST_PATH_IMAGE013
The number of the types of the delay chains,
Figure 620566DEST_PATH_IMAGE009
is the node class number.
The classification result is described by using the following delay chain classification table.
Trigger mode class 1, sensor node: time-triggered, controller node: time triggering, an actuator node: triggering time;
trigger mode class 2, sensor node: time-triggered, controller node: time triggering, an actuator node: triggering an event;
trigger mode class 3, sensor node: time-triggered, controller node: event triggering, an actuator node: triggering time;
trigger mode class 4, sensor node: time-triggered, controller node: event triggering, an actuator node: and triggering an event.
The classification result is described by using the following delay chain classification table.
Delay chain class table
Figure 23735DEST_PATH_IMAGE015
Step (ii) of
Figure 375082DEST_PATH_IMAGE003
The loop delay envelope analysis means that a delay upper bound function is utilized to determine the delay upper bound of a control loop delay chain of the networked motion control system of the electric automobile. The delay upper bound function comprises a local delay upper bound function and a global delay upper bound function, the local delay upper bound function is used for analyzing the delay upper bound of a control loop delay chain of a specific networked motion control system of the electric automobile, and the expression of the delay upper bound function is as follows:
Figure 196407DEST_PATH_IMAGE017
wherein the content of the first and second substances,
Figure 607797DEST_PATH_IMAGE018
is a supremum operator;
Figure 311311DEST_PATH_IMAGE019
respectively representing the number of network nodes in a single control loop and all control loopsThe number of delay chains corresponding to the path;
Figure 450037DEST_PATH_IMAGE020
a local delay upper bound is indicated,
Figure 125869DEST_PATH_IMAGE021
indicates a particular delay chain length;
Figure 708160DEST_PATH_IMAGE022
indicating the first in the control loop
Figure 102232DEST_PATH_IMAGE024
Each network node delays the component length.
The global delay upper bound function is the maximum value of the delay chain delay upper bound of all networked motion control system control loops of the electric automobile, and the expression is as follows:
Figure 592119DEST_PATH_IMAGE026
wherein the content of the first and second substances,
Figure 371725DEST_PATH_IMAGE018
is a supremum operator;
Figure 859338DEST_PATH_IMAGE019
respectively representing the number of network nodes in a single control loop and the number of delay chains corresponding to all control loops;
Figure 740707DEST_PATH_IMAGE027
respectively representing a local delay upper bound and a global delay upper bound,
Figure 237547DEST_PATH_IMAGE028
represents a maximum value of a specific delay chain length;
Figure 684709DEST_PATH_IMAGE029
to representIn the control loop
Figure 592491DEST_PATH_IMAGE030
Each network node delays the component length.
The invention has the beneficial effects that:
the invention provides a time delay analysis method for a network composite structure loop of a networked motion control system of an electric automobile, which is used as a set of complete control system time delay analysis methodology and can accurately analyze the maximum time delay in a control loop of a specific networked motion control system or all networked motion control systems in the electric automobile and provide theoretical support for analysis and design of a network time delay dynamic control system of the electric automobile, thereby providing technical support for improving the real-time property and the system stability of a controller and further improving the running safety of the automobile.
Drawings
FIG. 1 is a schematic diagram of a networked motion control system for an electric vehicle according to the present invention;
FIG. 2 is a control schematic diagram of the networked power train motion control system of the electric vehicle according to the present invention;
FIG. 3 is a diagram of a networked power train motion control system of an electric vehicle according to the present invention;
FIG. 4 is a schematic diagram of a delay cell according to the present invention;
FIG. 5 is a schematic view of a delay assembly of the present invention;
FIG. 6 is a schematic diagram of a delay chain of the networked power chain motion control system of the electric vehicle according to the present invention;
FIG. 7 is a schematic diagram of the delay upper bound of the networked power chain motion control system of the electric vehicle according to the present invention.
Detailed Description
The technical solutions of the present invention are further described in detail below with reference to the accompanying drawings, but the scope of the present invention is not limited to the following.
As shown in fig. 1, the networked motion control system for the electric vehicle adopts a line control technology and a vehicle-mounted network to acquire sensor signals and send control signals, replaces the traditional mechanical and hydraulic devices, has the characteristics of small volume, flexible arrangement, good controllability, high response speed and the like, and can realize good motion control performance of the electric vehicle.
As shown in fig. 2, the application of the method for analyzing the time lag in the composite structure loop of the networked motion control system of the electric vehicle is described by taking the networked power train motion control of the electric vehicle as an example.
In order to improve the smoothness and stability of the vehicle power chain, a networked power chain motion control system of the electric vehicle is constructed based on a line control technology and a vehicle-mounted network, as shown in fig. 2. The principle is as follows: the method comprises the steps that 4 sensors including a wheel speed sensor acquire state information of the wheel speed and the like of a vehicle, the state information is fed back to a power chain control unit through a vehicle-mounted network, the power chain control unit calculates a motor torque control command based on the feedback state information, the motor torque control command is sent to a motor control unit through the vehicle-mounted network, the motor torque is adjusted, and electric drive system vibration is restrained, so that the power chain control system becomes a typical networked motion control system.
As shown in fig. 3, the networked control system includes a power chain control unit, a motor output shaft corner sensor node, a transmission half-shaft corner sensor node, a wheel speed sensor node, and a motor rotation speed sensor node, wherein the motor output shaft corner sensor node, the transmission half-shaft corner sensor node, the wheel speed sensor node, the motor rotation speed sensor node, and the power chain control unit are connected through a vehicle-mounted network to form a feedback channel; the power chain control unit is connected with the motor control unit through a vehicle-mounted network to form a forward channel. According to a networked control theory, the use of a vehicle-mounted network inevitably introduces signal delay, and the signal delay directly influences the real-time performance of the motion control of a power chain of the electric automobile, so that the torsional vibration instability of a system is caused, the motion safety of the automobile is further influenced, and the method becomes a new challenge of the development of the high-performance transmission technology of the electric automobile.
To address the above challenges, it is a key technical challenge to accurately estimate the delay upper bound. The existing time delay analysis methods, such as a network deduction theory and a Markov time delay model, mostly focus on time delay analysis of partial links of a system, so that the estimation of an upper time delay bound is inaccurate, and the existing time delay analysis methods have certain limitations. Therefore, the invention provides a time-lag analysis method for a composite structure loop of a networked motion control system of an electric automobile, which can be used for analyzing the maximum time delay of the control loop of the networked motion control system of the electric automobile.
The method comprises the following three steps:
Figure 695576DEST_PATH_IMAGE001
analyzing related concepts and definitions in a time delay manner;
Figure 730528DEST_PATH_IMAGE002
analyzing the type of a delay system;
Figure 501038DEST_PATH_IMAGE003
and (4) loop delay envelope analysis. Wherein the steps
Figure 579722DEST_PATH_IMAGE001
The related concepts and definitions of the time delay analysis are steps
Figure 232420DEST_PATH_IMAGE002
Delayed system type identification and procedure
Figure 71063DEST_PATH_IMAGE003
The loop delay envelope analysis provides conceptual support; step (ii) of
Figure 164921DEST_PATH_IMAGE002
Utilizing the steps
Figure 430817DEST_PATH_IMAGE001
The related concepts are subjected to the statistics of the type of the delay system and are steps
Figure 757762DEST_PATH_IMAGE003
Providing a delayed envelope analysis object; step (ii) of
Figure 196834DEST_PATH_IMAGE003
Delay loop envelope utilization step
Figure 676356DEST_PATH_IMAGE001
Related concepts and steps
Figure 113154DEST_PATH_IMAGE002
And analyzing the object and deducing to obtain the mathematical expression of the upper limit of the loop delay of the system.
First, to analyze the loop maximum delay, a concept is defined: the method comprises the steps of a network node delay component, a control loop delay chain, delay chain type analysis and delay boundary envelope analysis.
The network node delay component is a description of a composite delay time of a network node.
The control loop delay chain is a description of the composite delay time of one control loop.
The type analysis of the delay chain is about the description of the type classification of various control loop delay chains composed of network nodes with different trigger modes.
The delay boundary envelope analysis is to find the description of the delay upper bound of the delay chain of the control loop.
As shown in fig. 4, to analyze the maximum delay of the control loop, a delay element definition is introduced: communication queue time, task execution time, communication queue time, and communication execution time are expressed by CQ, CI, TQ, and TI, respectively.
As shown in fig. 5, each network node delay component is composed of a task queuing time, a task execution time, a communication queuing time, and a communication execution time.
For the sensor node, in the time trigger mode, as shown in fig. 5 (1), its delay components include task execution time TI, communication queuing time CQ and communication execution time CI; in the event triggered mode, as shown in fig. 5 (2), the delay elements include a task execution time TI, a communication queuing time CQ, and a communication execution time CI.
For the controller node, in the time-triggered mode, as shown in fig. 5 (3), its delay elements include task queuing time TQ, task execution time TI, communication queuing time CQ, and communication execution time CI; in the event triggered mode, as shown in fig. 5 (4), the delay elements include a task execution time TI, a communication queuing time CQ, and a communication execution time CI.
For the executor node, in the time-triggered mode, as shown in fig. 5 (5), its delay components include task queuing time TQ and task execution time TI; in the event triggered mode, as shown in fig. 5 (6), the delay component includes a task execution time TI.
As shown in fig. 6, the control loop delay chain is generally composed of network node delay components connected by inter-node channels, wherein the types of network nodes include sensor nodes, controller nodes and actuator nodes. The inter-node path includes a forward path and a feedback path. The loop delay chain length formula is as follows:
Figure 412548DEST_PATH_IMAGE032
wherein
Figure 842262DEST_PATH_IMAGE033
Indicating the first in the control loop
Figure 176291DEST_PATH_IMAGE034
The length of the delay element of each network node,
Figure 580727DEST_PATH_IMAGE035
indicating the number of network nodes in the control loop,
Figure 632997DEST_PATH_IMAGE036
。
the delay system type analysis process refers to the induction and classification of the delay chain of the control loop based on the node driving mode, and the number of types of the delay chain meets the following formula:
Figure 85975DEST_PATH_IMAGE037
wherein
Figure 789358DEST_PATH_IMAGE038
The number of the types of the delay chains,
Figure 567958DEST_PATH_IMAGE039
is the node class number. As shown in fig. 6, the network nodes of the case system include three types: sensor nodes, controller nodes and actuator nodes, i.e.
Figure 904261DEST_PATH_IMAGE040
Then, then
Figure 426510DEST_PATH_IMAGE041
The classification result can be described by using a delay chain classification table as follows:
delay chain class table
Figure 735131DEST_PATH_IMAGE043
The loop delay envelope analysis means that a delay upper bound function is utilized to determine the delay upper bound of a control loop delay chain of the networked motion control system of the electric automobile. The delay upper bound function comprises a local delay upper bound function and a global delay upper bound function.
The local delay upper bound function is used for analyzing the delay upper bound of a control loop delay chain of a specific networked motion control system of the electric automobile, and the expression of the local delay upper bound function is as follows:
Figure 668321DEST_PATH_IMAGE045
wherein the content of the first and second substances,
Figure 429604DEST_PATH_IMAGE046
is a supremum operator;
Figure 552280DEST_PATH_IMAGE047
respectively representing the number of network nodes in a single control loop and the number of delay chains corresponding to all control loops;
Figure 715409DEST_PATH_IMAGE049
a local delay upper bound is indicated,
Figure 835811DEST_PATH_IMAGE051
indicates a particular delay chain length;
Figure 333658DEST_PATH_IMAGE053
indicating the first in the control loop
Figure 197708DEST_PATH_IMAGE054
Each network node delays the component length.
The global delay upper bound function is the maximum value of the delay chain delay upper bound of all networked motion control system control loops of the electric automobile, and the expression is as follows:
Figure 215343DEST_PATH_IMAGE056
wherein the content of the first and second substances,
Figure 568964DEST_PATH_IMAGE057
is a supremum operator;
Figure 304839DEST_PATH_IMAGE047
respectively representing the number of network nodes in a single control loop and the number of delay chains corresponding to all control loops;
Figure 425110DEST_PATH_IMAGE059
respectively representing a local delay upper bound and a global delay upper bound,
Figure DEST_PATH_IMAGE060
represents a maximum value of a specific delay chain length;
Figure DEST_PATH_IMAGE062
indicating the first in the control loop
Figure 766093DEST_PATH_IMAGE063
Length of delay element of network node
To analyze the control loop maximum delay, the following assumptions are made: (1) the time triggers the sampling of the sensor node and sends the sampling result to the controller node through the CAN; (2) the time trigger controller node calculates a motor torque command according to a sampling result from the sensor node and periodically sends the motor torque command to the motor controller node; (3) when the event trigger motor controller node receives the motor torque command information, the event trigger motor controller node immediately controls the driving motor to execute corresponding actions.
Based on the concepts and assumptions above, the analysis of the upper bound of delay of the control loop of the networked power train control system of the electric vehicle is as follows: as shown in fig. 7, the loop delay of the composite structure can be expressed by the following formula:
Figure 743145DEST_PATH_IMAGE065
the upper delay bound can be calculated by the following formula:
Figure 966316DEST_PATH_IMAGE067
Figure 968907DEST_PATH_IMAGE069
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE070
represents the time delay of the composite structure loop of the networked power chain control system of the electric automobile,
Figure 164396DEST_PATH_IMAGE039
the number of network nodes in the networked power chain control system of the electric automobile is shown,
Figure DEST_PATH_IMAGE072
indicating the first in the control loop
Figure 781191DEST_PATH_IMAGE063
The length of the delay element of each network node,
Figure 226079DEST_PATH_IMAGE073
indicates the length of the sensor task execution time TI,
Figure DEST_PATH_IMAGE074
representing the sum of the sensor communication queuing time CQ and the communication execution time CI length,
Figure 501203DEST_PATH_IMAGE075
indicating the length of the controller task queue time TQ,
Figure DEST_PATH_IMAGE076
indicating the length of the controller task execution time TI,
Figure 66045DEST_PATH_IMAGE077
representing the sum of the lengths of the controller communication queuing time CQ and the communication execution time CI,
Figure DEST_PATH_IMAGE078
indicating the length of the executor task execution time TI,
Figure 135632DEST_PATH_IMAGE079
representing the system cycle.
The above description is only an example of the present invention, and the present invention is not limited to the above embodiment, and all the modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (10)

1. The time lag analysis method for the composite structure loop of the networked motion control system of the electric automobile is characterized by comprising the following steps of: the method comprises the following steps:
Figure 764034DEST_PATH_IMAGE001
analyzing related concepts and definitions in a time delay manner;
Figure 353279DEST_PATH_IMAGE002
analyzing the type of a delay system; (3) loop delay envelope analysis;
wherein the steps
Figure 851125DEST_PATH_IMAGE001
The related concepts and definitions of the time delay analysis are steps
Figure 715176DEST_PATH_IMAGE002
Delayed system type identification and procedure
Figure 998390DEST_PATH_IMAGE003
The loop delay envelope analysis provides conceptual support;
step (ii) of
Figure 289694DEST_PATH_IMAGE002
Utilizing the steps
Figure 274836DEST_PATH_IMAGE001
The related concepts are subjected to the statistics of the type of the delay system and are steps
Figure 942578DEST_PATH_IMAGE003
Providing a delayed envelope analysis object;
step (ii) of
Figure 80298DEST_PATH_IMAGE003
Delay loop envelope utilization step
Figure 339241DEST_PATH_IMAGE001
Related concepts and steps
Figure 562412DEST_PATH_IMAGE002
And analyzing the object and deducing to obtain the mathematical expression of the upper limit of the loop delay of the system.
2. The electric vehicle networked motion control system composite structure loop time lag analysis method according to claim 1, characterized in that: step (ii) of
Figure 17533DEST_PATH_IMAGE001
The related concepts and definitions of the delay analysis comprise four concepts which are respectively a network node delay component, a control loop delay chain, a delay chain type analysis and a delay boundary envelope analysis;
the network node delay component is used for describing the composite delay time of one network node;
the control loop delay chain is used for describing the composite delay time of one control loop;
the type analysis of the delay chain is about the description of the type classification of various control loop delay chains composed of network nodes with different trigger modes;
the delay boundary envelope analysis is to find the description of the delay upper bound of the delay chain of the control loop.
3. The electric vehicle networked motion control system composite structure loop time lag analysis method according to claim 2, characterized in that: the network node delay component;
the system consists of task queuing time, task execution time, communication queuing time and communication execution time; the task queuing time, the task execution time, the communication queuing time and the communication execution time are delay elements.
4. The electric vehicle networked motion control system composite structure loop time lag analysis method according to claim 3, characterized in that: the network node delay assembly comprises a sensor node, a controller node and an actuator node, wherein the network node type comprises the following types:
for the sensor node, in the time trigger mode, the delay component comprises task execution time, communication queuing time and communication execution time; in the event trigger mode, the delay assembly comprises task execution time, communication queuing time and communication execution time;
for the controller node, in a time trigger mode, the delay assembly comprises task queuing time, task execution time, communication queuing time and communication execution time; in the event trigger mode, the delay assembly comprises task execution time, communication queuing time and communication execution time;
for an actuator node, under a time trigger mode, a delay assembly of the actuator node comprises task queuing time and task execution time; in the event trigger mode, the delay component comprises task execution time.
5. The electric vehicle networked motion control system composite structure loop time lag analysis method according to claim 2, characterized in that: the control loop delay chain is formed by connecting network node delay components through channels among nodes, wherein the network nodes comprise sensor nodes, controller nodes and actuator nodes; the inter-node path includes a forward path and a feedback path.
6. The electric vehicle networked motion control system composite structure loop time lag analysis method according to claim 5, characterized in that: the control loop delay chain length formula is as follows:
Figure 9760DEST_PATH_IMAGE005
wherein
Figure 908446DEST_PATH_IMAGE006
Indicating the first in the control loop
Figure 618913DEST_PATH_IMAGE008
The length of the delay element of each network node,
Figure 346566DEST_PATH_IMAGE009
indicating the number of network nodes in the control loop,
Figure 458879DEST_PATH_IMAGE010
。
7. the electric vehicle networked motion control system composite structure loop time lag analysis method according to claim 1, characterized in that: step (ii) of
Figure 528466DEST_PATH_IMAGE002
The delay system type analysis refers to induction and classification of the control loop delay chain based on a node driving mode;
the number of types of the control loop delay chains meets the following formula:
Figure 726229DEST_PATH_IMAGE011
wherein
Figure 523153DEST_PATH_IMAGE013
The number of the types of the delay chains,
Figure 224392DEST_PATH_IMAGE009
is the node class number;
and the classification result is described by adopting a delay chain classification table:
trigger mode class 1, sensor node: time-triggered, controller node: time triggering, an actuator node: triggering time;
trigger mode class 2, sensor node: time-triggered, controller node: time triggering, an actuator node: triggering an event;
trigger mode class 3, sensor node: time-triggered, controller node: event triggering, an actuator node: triggering time;
trigger mode class 4, sensor node: time-triggered, controller node: event triggering, an actuator node: and triggering an event.
8. The electric vehicle networked motion control system composite structure loop time lag analysis method according to claim 1, characterized in that: step (ii) of
Figure 464881DEST_PATH_IMAGE003
The loop delay envelope analysis means that a delay upper bound function is utilized to determine the delay upper bound of a control loop delay chain of the networked motion control system of the electric automobile; the delay upper bound function comprises a local delay upper bound function and a global delay upper bound function.
9. The electric vehicle networked motion control system composite structure loop time lag analysis method according to claim 8, characterized in that: the local delay upper bound function is used for analyzing the delay upper bound of a delay chain of a control loop of a specific networked motion control system of the electric automobile, and the expression of the local delay upper bound function is as follows:
Figure 884361DEST_PATH_IMAGE015
；
wherein the content of the first and second substances,
Figure 484975DEST_PATH_IMAGE016
is a supremum operator;
Figure 306301DEST_PATH_IMAGE017
respectively representing the number of network nodes in a single control loop and the number of delay chains corresponding to all control loops;
Figure 717691DEST_PATH_IMAGE018
a local delay upper bound is indicated,
Figure 624467DEST_PATH_IMAGE019
indicates a particular delay chain length;
Figure 310663DEST_PATH_IMAGE020
indicating the length of the delay element of the first network node in the control loop.
10. The electric vehicle networked motion control system composite structure loop time lag analysis method according to claim 8, characterized in that: the global delay upper bound function is the maximum value of the delay upper bound of the delay chain of the control loop of the networked motion control system for analyzing the electric automobile, and the expression is as follows:
Figure 704604DEST_PATH_IMAGE022
wherein the content of the first and second substances,
Figure 286895DEST_PATH_IMAGE016
is a supremum operator;
Figure 477705DEST_PATH_IMAGE017
respectively representing the number of network nodes in a single control loop and the number of delay chains corresponding to all control loops;
Figure DEST_PATH_IMAGE023
respectively representing a local delay upper bound and a global delay upper bound,
Figure 888964DEST_PATH_IMAGE024
represents a maximum value of a specific delay chain length;
Figure DEST_PATH_IMAGE025
indicating the first in the control loop
Figure 888144DEST_PATH_IMAGE026
Each network node delays the component length.
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