CAN bus physical layer path planning optimization method and system

Abstract

The invention discloses a CAN bus physical layer path planning optimization method and system, and the method comprises the following steps: a whole vehicle network is divided into n network segments, m network nodes exist in a network segment i, i1 and im are nodes at the head end and the tail end of each network segment, p trunk nodes exist in each network segment, q branch nodes exist in each network segment, and m = p + q; establishing a first objective function about the physical layer path length of a single network segment, and setting a first constraint condition; solving the first objective function by using an iteration method, and outputting a minimum first objective function value; planning a physical layer path of each network segment based on the first objective function value; and planning the physical layer path of the whole vehicle based on the planning of the physical layer path of each network segment. According to the method, the first constraint condition is set, the objective function is solved by using the successive attempt method, and the minimum objective function value is output, so that the physical layer path is planned, manual one-by-one adjustment is not needed, and the efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle physical layer optimization, and in particular to a CAN bus physical layer path planning optimization method and system. Background Art

[0002] At present, with the rapid development of the automobile industry and electrical information technology, the number of electronic control units (ECUs) in vehicles is also increasing, and the interactive signals between ECU nodes are becoming more and more complex. Since the controller area network CAN bus communication can realize the distributed control of electronic control units, it can reduce the layout of the wiring harness on the vehicle and reduce costs. CAN bus communication has gradually become the main communication bus between various ECUs in the automotive industry. The existing methods rely on previous design experience to determine the physical layer path of the vehicle CAN bus, and often need to be adjusted manually one by one, which is not only inefficient, but also ultimately impossible to verify.

[0003] Therefore, it is urgent to propose a new solution to solve the above problems. Summary of the invention

[0004] The present invention provides a CAN bus physical layer path planning optimization method and system, which solves the problem that the prior art needs to adjust manually one by one, which is not only inefficient but also ultimately impossible to verify.

[0005] The present invention provides a CAN bus physical layer path planning optimization method, comprising the following steps:

[0006] The vehicle network is divided into n segments (1, ..., i, ..., n), where there are m network nodes (i 1 ,…,i m ),i 1 and i m The nodes at the beginning and end of each network segment, such as Figure 3 As shown, there are p trunk nodes and q branch nodes in each network segment, and m = p + q;

[0007] Establishing a first objective function regarding the physical layer path length of a single network segment and setting a first constraint condition;

[0008] Solving the first objective function by using an iterative method and outputting the minimum first objective function value;

[0009] Based on the first objective function value, plan the physical layer path of each network segment;

[0010] The physical layer path of the entire vehicle is planned based on the physical layer path planning of each network segment.

[0011] Furthermore, the first objective function is

[0012] Among them, M i is the physical layer path length of a single network segment, L is the total length of p trunk nodes, S is the total length of q branch nodes, l j#j+1 Represents two adjacent backbone nodes l j and l j+1 The length of the transmission medium between two adjacent nodes in the path is l, 1≤j≤p-1, 2≤p≤m, j#j+1 Determined by the current path of the backbone node and the physical topology of the harness, s k is the physical layer path length of the kth branch node, 1≤k≤q.

[0013] Furthermore, the first constraint condition includes:

[0014] The total length of p trunk nodes L≤40m;

[0015] The physical layer path length s of each branch node k k ≤1m, where 0≤k≤q.

[0016] Furthermore, the first constraint condition also includes:

[0017] Each network segment must be connected to its designated source and destination nodes;

[0018] The paths of the various network segments must follow the physical layout inside the vehicle.

[0019] Further, the method of solving the first objective function by iteration and outputting the minimum first objective function value includes:

[0020] Calculate the value of the first objective function for each different p value, and select the p value corresponding to the minimum value of the first objective function.

[0021] Further, the planning of the physical layer path of each network segment based on the first objective function value includes:

[0022] Determine the order of the backbone nodes for each network segment and the locations of the backbone nodes and branch nodes.

[0023] Furthermore, the physical layer path planning of the whole vehicle based on the physical layer path planning of each network segment includes the following steps:

[0024] Establish the second objective function, Among them, M T is the sum of the physical layer path lengths of all n network segments;

[0025] Set the second constraint;

[0026] Find the minimum value of the second objective function.

[0027] Furthermore, the second constraint condition includes:

[0028] For the path intersections between two network segments, a gateway is used to manage the intersections;

[0029] Meet the physical topology of the vehicle's space harness;

[0030] The physical layer path length s of each branch node k k ≤1m, where 0≤k≤q.

[0031] Furthermore, after the physical layer path planning of the whole vehicle is performed based on the physical layer path planning of each network segment, the following further includes:

[0032] The physical layer path planning of the whole vehicle is verified by simulation software. If the verification fails, the process returns to the step of re-planning the physical layer path of the whole vehicle based on the physical layer path of each network segment until the verification passes.

[0033] The present invention also provides a CAN bus physical layer path planning optimization system, comprising:

[0034] A first objective function acquisition module, used to establish a first objective function about the physical layer path length of a single network segment and set a first constraint condition;

[0035] A first objective function value acquisition module, used to solve the first objective function by using an iterative method and output a minimum first objective function value;

[0036] Each network segment acquisition module is used to plan the physical layer path of each network segment based on the first objective function value;

[0037] The vehicle physical layer path acquisition module is used to plan the vehicle physical layer path based on the planning of the physical layer paths of each network segment.

[0038] Compared with the prior art, the CAN bus physical layer path planning optimization method of the present invention establishes an objective function of the physical layer path length of a single network segment, sets a first constraint condition, uses a successive trial method to solve the objective function, and outputs the minimum objective function value, thereby planning the physical layer path. There is no need for manual adjustments one by one, which reduces manual workload, improves design efficiency by 50%, improves accuracy by 60%, and saves 1% on average material cost per vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 A network topology diagram of two network segments of the present invention;

[0040] Figure 2 This is an example diagram of the physical topology of the vehicle wiring harness of the present invention;

[0041] Figure 3 It is a detailed node schematic diagram of the present invention;

[0042] Figure 4 It is a specific connection diagram of each backbone node in a single network segment of the present invention. DETAILED DESCRIPTION

[0043] In order to further understand the content, features and effects of the present invention, the following embodiments are given together with the attached Figures 1 to 4 The detailed instructions are as follows.

[0044] like Figure 1 As shown in the figure, the CAN network segment is the part of the network nodes and transmission media that can communicate directly using the same physical layer device (transmission medium) in the CAN network. A network topology with two or more network segments requires a gateway (the green node in the figure) to complete signal forwarding, that is, the signal interaction between network segments 1 and 2, with the node with terminal resistor as the end node. Figure 1 There are two end nodes in each of the network segments 1 and 2. The CAN bus physical layer transmission medium is reflected in the physical topology of the vehicle wiring harness in the form of wires. The physical layer path of the CAN bus is calculated with the determined physical topology of the vehicle wiring harness as input.

[0045] This embodiment provides a CAN bus physical layer path planning optimization method, including the following steps:

[0046] S1. Divide the vehicle network into n segments (1, ..., i, ..., n), where there are m network nodes (i 1 ,…,i m ),i 1 and i m The nodes at the beginning and end of each network segment, where there are p trunk nodes and q branch nodes in each network segment, m = p + q;

[0047] S2. Establishing a first objective function regarding the physical layer path length of a single network segment and setting a first constraint condition;

[0048] S3, solving the first objective function by using an iterative method, and outputting the minimum first objective function value;

[0049] S4. Based on the first objective function value, plan the physical layer path of each network segment;

[0050] S5. Plan the physical layer path of the entire vehicle based on the planning of the physical layer paths of each network segment.

[0051] The CAN bus physical layer path planning optimization method of the present invention establishes an objective function of the physical layer path length of a single network segment, sets a first constraint condition, solves the objective function using a successive trial method, and outputs a minimum objective function value, thereby planning the physical layer path without the need for manual adjustments one by one, reducing manual workload, improving design efficiency by 50%, improving accuracy by 60%, and saving 1% on average material cost per vehicle.

[0052] In this embodiment, the first objective function is:

[0053]

[0054] Among them, M i is the physical layer path length of a single network segment, L is the total length of p trunk nodes, S is the total length of q branch nodes, l j#j+1 Represents two adjacent backbone nodes l j and l j+1 The length of the transmission medium between two adjacent nodes in the path is l, 1≤j≤p-1, 2≤p≤m, j#j+1 Determined by the current path of the backbone node and the physical topology of the harness, s k is the physical layer path length of the kth branch node, 1≤k≤q. In this embodiment, the first constraint condition includes:

[0055] The total length of p trunk nodes L≤40m;

[0056] The physical layer path length s of each branch node k k ≤1m, where 0≤k≤q.

[0057] In this embodiment, the first constraint condition also includes:

[0058] Each network segment must be connected to its designated source and destination nodes;

[0059] The paths of the various network segments must follow the physical layout inside the vehicle.

[0060] In this embodiment, solving the first objective function by iteration and outputting the minimum first objective function value includes:

[0061] The values ​​of the first objective function under different p values ​​are calculated respectively, and the p value corresponding to the minimum value of the first objective function is selected. Specifically, the value of the objective function is calculated from the case of p=2, q=m-2, where p=2, q=m-2 corresponds to the corresponding physical layer topology (including the location and order of the nodes), and then p=3, q=m-3, ..., p=m, q=0 is calculated. Finally, m-1 results (the values ​​of the objective function) can be obtained, and the p and q corresponding to the minimum value of the m-1 results are output. In this embodiment, the minimum value corresponds to p=4, q=7-4=3, m=7, and the physical layer topology corresponding to p=4, q=3 can be determined.

[0062] In this embodiment, the planning of the physical layer path of each network segment based on the first objective function value includes:

[0063] In this embodiment, the physical layer path planning of the whole vehicle based on the physical layer path planning of each network segment includes the following steps:

[0064] Establish the second objective function, Among them, M T is the sum of the physical layer path lengths of all n network segments;

[0065] Set the second constraint;

[0066] Find the minimum value of the second objective function.

[0067] Determine the order of the backbone nodes of each network segment and the spatial locations of the backbone nodes and branch nodes. By obtaining the p and q corresponding to each network segment and the corresponding physical layer topology, the specific values ​​of p and q for each network segment may be different. Figure 3 As shown in the figure, there are five backbone nodes in the network segment, including two at the head and tail, and three backbone nodes A, B and C in the middle. When inputting the p and q of each network segment, the order of the backbone nodes corresponding to this p and q will also be set synchronously. The connection order between the two backbone nodes at the head and tail of a single network segment and other network segments is fixed, and there are a total of 6 permutations and combinations of the three backbone nodes in the middle. The sum of the physical layer path lengths of all n network segments under various permutations and combinations is calculated by iterative method, and the minimum value is obtained. In addition, the adjacent network segments are connected through pre-set gateways. Figure 2 In the figure, the blue highlighted part is the physical topology of the vehicle wiring harness, and the ends of some branches are the network nodes in the network topology diagram.

[0068] In this embodiment, the second constraint condition includes:

[0069] For the path intersections between two network segments, a gateway is used to manage the intersections;

[0070] Meet the physical topology of the vehicle's space harness;

[0071] The physical layer path length s of each branch node k k ≤1m, where 0≤k≤q.

[0072] This embodiment obtains the sum of the physical layer path lengths of all n network segments by setting the second constraint condition.

[0073] In this embodiment, after the physical layer path planning of the whole vehicle is performed based on the physical layer path planning of each network segment, the following further includes:

[0074] The physical layer path planning of the whole vehicle is verified by simulation software. If the verification fails, the process returns to the step of re-planning the physical layer path based on each network segment until the verification passes, thus ensuring the reliability of the result.

[0075] The present invention also provides a CAN bus physical layer path planning optimization system, comprising:

[0076] A first objective function acquisition module, used to establish a first objective function about the physical layer path length of a single network segment and set a first constraint condition;

[0077] A first objective function value acquisition module, used to solve the first objective function by using an iterative method and output a minimum first objective function value;

[0078] Each network segment acquisition module is used to plan the physical layer path of each network segment based on the first objective function value;

[0079] The vehicle physical layer path acquisition module is used to plan the vehicle physical layer path based on the planning of the physical layer paths of each network segment.

[0080] The CAN bus physical layer path planning optimization system of the present invention establishes an objective function of the physical layer path length of a single network segment, sets a first constraint condition, solves the objective function using a successive trial method, and outputs the minimum objective function value, thereby planning the physical layer path.

[0081] The invention described above only expresses the implementation methods of the embodiments of the present invention, and cannot be understood as limiting the scope of the invention patent, nor does it impose any form of limitation on the structure of the embodiments of the present invention. It should be pointed out that for ordinary technicians in this field, several changes and improvements can be made without departing from the concept of the embodiments of the present invention, which all belong to the protection scope of the embodiments of the present invention.

Claims

1. A CAN bus physical layer path planning optimization method, characterized in that: The following steps are involved: The vehicle network is divided into n segments (1, ..., i, ..., n), where there are m network nodes (i1, ..., i m ), i1 and i m The nodes at the beginning and end of each network segment, where there are p trunk nodes and q branch nodes in each network segment, m = p + q; Establishing a first objective function regarding the physical layer path length of a single network segment and setting a first constraint condition; Solving the first objective function by using an iterative method and outputting the minimum first objective function value; Based on the first objective function value, plan the physical layer path of each network segment; The physical layer path of the entire vehicle is planned based on the physical layer path planning of each network segment.

2. A CAN bus physical layer path planning optimization method according to claim 1, characterized in that: The first objective function is, Among them, M i is the physical layer path length of a single network segment, L is the total length of p trunk nodes, S is the total length of q branch nodes, l j#j+1 Represents two adjacent backbone nodes l j and l j+1 The length of the transmission medium between two adjacent nodes in the path is l, 1≤j≤p-1, 2≤p≤m, j#j+1 Determined by the current path of the backbone node and the physical topology of the harness, s k is the physical layer path length of the kth branch node, 1≤k≤q.

3. A CAN bus physical layer path planning optimization method according to claim 2, characterized in that: The first constraint condition includes: The total length of p trunk nodes L≤40m; The physical layer path length s of each branch node k k ≤1m, where 0≤k≤q.

4. A CAN bus physical layer path planning optimization method according to claim 3, characterized in that: The first constraint condition also includes: Each network segment must be connected to its designated source and destination nodes; The paths of the various network segments must follow the physical layout inside the vehicle.

5. A CAN bus physical layer path planning optimization method according to claim 4, characterized in that: The method of solving the first objective function by iteration and outputting the minimum first objective function value includes: Calculate the value of the first objective function for each different p value, and select the p value corresponding to the minimum value of the first objective function.

6. A CAN bus physical layer path planning optimization method according to claim 4, characterized in that: The planning of the physical layer path of each network segment based on the first objective function value includes: Determine the order of the backbone nodes for each network segment and the locations of the backbone nodes and branch nodes.

7. A CAN bus physical layer path planning optimization method according to claim 4, characterized in that: The physical layer path planning of the whole vehicle based on the physical layer path planning of each network segment includes the following steps: Establish the second objective function, Among them, M T is the sum of the physical layer path lengths of all n network segments; Set the second constraint; Find the minimum value of the second objective function.

8. A CAN bus physical layer path planning optimization method according to claim 3, characterized in that: The second constraint condition includes: For the path intersections between two network segments, a gateway is used to manage the intersections; Meet the physical topology of the vehicle's space harness; The physical layer path length s of each branch node k k ≤1m, where 0≤k≤q.

9. A CAN bus physical layer path planning optimization method according to claim 3, characterized in that: After the physical layer path planning of the whole vehicle is performed based on the physical layer path planning of each network segment, the method further includes: The physical layer path planning of the whole vehicle is verified by simulation software. If the verification fails, the process returns to the step of re-planning the physical layer path of the whole vehicle based on the physical layer path of each network segment until the verification passes.

10. A CAN bus physical layer path planning optimization system, characterized in that: include: A first objective function acquisition module, used to establish a first objective function about the physical layer path length of a single network segment and set a first constraint condition; A first objective function value acquisition module, used to solve the first objective function by using an iterative method and output a minimum first objective function value; Each network segment acquisition module is used to plan the physical layer path of each network segment based on the first objective function value; The vehicle physical layer path acquisition module is used to plan the vehicle physical layer path based on the planning of the physical layer paths of each network segment.

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