Intelligent vehicle driving method and system based on DSP

Abstract

The invention provides an intelligent vehicle driving method and system based on a DSP, the driving method is applied to an intelligent vehicle, the intelligent vehicle comprises four driving motors and a main controller, the driving motors are in one-to-one correspondence with wheels and are in transmission connection with the wheels, and the main controller is in communication connection with DSP controllers of the driving motors; comprising the steps of calling a driving control library according to current vehicle state data; according to the current vehicle working condition state, a control parameter set is called from a drive control library; and generating control parameters corresponding to the controllers according to the control parameter set. According to the intelligent vehicle driving method and system based on the DSP, the vehicle state data and the vehicle working condition state are comprehensively analyzed, accurate control parameters are determined on the basis of comprehensive analysis, and therefore efficient utilization of vehicle power and accurate control over the vehicle are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy vehicle driving, and in particular to a DSP-based intelligent vehicle driving method and system. Background Art

[0002] New energy vehicles have advantages over fuel vehicles in terms of energy and environment. Electric vehicles are a type of new energy vehicle, and they are also the most advantageous in terms of energy efficiency. Electric vehicles are vehicles that use onboard power as a power source and are required to meet road traffic and safety requirements.

[0003] The driving mode of four-wheel independent drive electric vehicles is that four independent motors provide power to the four wheels respectively. Because there is no need to distribute power to the four wheels and eliminate the transmission shaft and other components of traditional fuel vehicles, the structure of the vehicle is simpler and the layout is more flexible. It is precisely because of the rigid structural advantages compared with traditional fuel vehicles that the system layout and space utilization of the vehicle are more free. However, due to the existence of four motors, that is, four power sources, how to coordinate and control to achieve efficient use of vehicle power and precise control of the vehicle has always been a technical problem that needs to be solved urgently. Summary of the invention

[0004] One of the purposes of the present invention is to provide a DSP-based intelligent vehicle driving method and system, which comprehensively analyzes vehicle status data and vehicle operating conditions, and accurately determines control parameters based on the comprehensive analysis, thereby achieving efficient use of vehicle power and precise control of the vehicle.

[0005] A DSP-based smart car driving method provided in an embodiment of the present invention is applied to a smart car, wherein the smart car comprises: four drive motors and a main controller, wherein the drive motors correspond to the wheels one by one and are transmission-connected, and the main controller is communicatively connected with the DSP controllers of the drive motors; and comprises:

[0006] According to the current vehicle status data, the drive control library is retrieved;

[0007] According to the current vehicle operating state, the control parameter set is retrieved from the drive control library;

[0008] According to the control parameter set, the control parameters corresponding to each controller are generated.

[0009] Preferably, the drive motor comprises a wheel-side motor.

[0010] Preferably, the communication method between the main controller and the DSP controller of the drive motor includes: CAN bus communication.

[0011] Preferably, the vehicle status data includes: the load at each pre-divided area location.

[0012] Preferably, the vehicle operating status includes one or more combinations of vehicle speed, acceleration, steering wheel angle, tire wear, road surface type, and road conditions.

[0013] The present invention also provides a DSP-based smart car drive system, which is applied to a smart car. The smart car includes: four drive motors and a main controller, the drive motors correspond to the wheels one by one and are transmission connected, and the main controller is communicatively connected to the DSP controllers of each drive motor; including: a first analysis module, a second analysis module and a generation module; wherein the first analysis module retrieves a drive control library based on current vehicle status data; the second analysis module retrieves a control parameter set from the drive control library based on the current vehicle operating condition; and the generation module generates control parameters corresponding to each controller based on the control parameter set.

[0014] Preferably, the drive motor comprises a wheel-side motor.

[0015] Preferably, the communication method between the main controller and the DSP controller of the drive motor includes: CAN bus communication.

[0016] Preferably, the vehicle status data includes: the load at each pre-divided area location.

[0017] Preferably, the vehicle operating status includes one or more combinations of vehicle speed, acceleration, steering wheel angle, tire wear, road surface type, and road conditions.

[0018] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0019] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0021] Figure 1 A schematic diagram of a DSP-based smart car driving method according to an embodiment of the present invention;

[0022] Figure 2 The figure is a schematic diagram of the arrangement of the wheel side motor in an embodiment of the present invention;

[0023] Figure 3 Schematic diagram of a DSP-based smart car driving system in an embodiment of the present invention. DETAILED DESCRIPTION

[0024] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0025] The embodiment of the present invention provides a DSP-based smart car driving method, which is applied to a smart car, wherein the smart car comprises: four drive motors and a main controller, wherein the drive motors correspond to the wheels one by one and are transmission-connected, and the main controller is communicatively connected with the DSP controllers of the drive motors;

[0026] like Figure 1 As shown, the DSP-based smart car driving method includes:

[0027] Step 1: Retrieve the drive control library based on the current vehicle status data;

[0028] After the design and production of various types of vehicles, their structures, weights and other properties are fixed. Therefore, when constructing the drive control library, such properties can be used as fixed items, which will basically have no impact on the drive control. Therefore, only the vehicle status data that cannot be fixed (that is, the vehicle status data that will change when the vehicle is in use) needs to be considered. When configuring the drive control library for different types of vehicles, only the drive control library corresponding to the different states of the vehicle status data that will change when the vehicle is in use needs to be configured. When the vehicle is in use, the drive control is first retrieved from the pre-stored multiple drive control libraries based on the vehicle status data, where the vehicle status data includes: the load at each pre-divided area position;

[0029] Step 2: According to the current vehicle operating state, a control parameter set is retrieved from the drive control library;

[0030] The current vehicle operating state indicates the current vehicle driving environment, and a control parameter set suitable for the current driving environment is retrieved from the drive control library according to the current vehicle driving environment; wherein the vehicle operating state includes: one or more combinations of vehicle speed, acceleration, steering wheel angle, tire wear, road type, and road condition;

[0031] Step 3: Generate control parameters corresponding to each controller based on the control parameter set.

[0032] The control parameter set includes the data corresponding to the control parameters of each controller; directly extract the data corresponding to each controller in the control parameter set, and use the extracted data as the control parameter. Comprehensively analyze the vehicle status data and vehicle operating conditions, and accurately determine the control parameters based on the comprehensive analysis, so as to achieve efficient use of vehicle power and precise control of the vehicle.

[0033] The DSP-based smart car driving method of this embodiment runs a program configured in the main controller of the smart car to realize comprehensive analysis of vehicle status data and vehicle operating status, and accurately determines control parameters based on the comprehensive analysis, thereby realizing efficient use of vehicle power and accurate control of the vehicle. In addition, the drive motor includes a wheel-side motor (such as Figure 2 The communication method between the main controller and the DSP controller of the drive motor includes: CAN bus communication; the DSP controller includes: TMS320F28335 chip.

[0034] In order to realize the calling of the drive control library, in one embodiment, the specific steps of calling the drive control library are as follows:

[0035] Step 11: Screening and extracting the vehicle status data to form a first status data group by orderly arranging the extracted data;

[0036] Considering the different spaces and usages inside the vehicle, the areas that may change are divided and numbered in sequence to form multiple pre-divided area positions. For example, the power battery is the area position numbered 1, the trunk part can be the area position numbered 2, each seat space can be a separate area position corresponding to area positions 3 to N, each storage groove in the space between the main driver's seat and the co-driver's seat can be a area position, and the storage space in front of the co-driver's seat can also be a area position;

[0037] The screening and extraction mainly extracts the load of each pre-divided regional position; the first state data group can be formed by arranging them in the order of regional position numbers;

[0038] Step 12: Match the first state data group with the first identification data group corresponding to each drive control library, and extract the drive control library associated with the first identification data group matching the first state data group.

[0039] Each drive control library is constructed by professionals through analysis of data after simulation tests of vehicles under different working conditions under various vehicle state data. During simulation, the simulation test data under different working conditions under the same vehicle state data are taken as a group to construct a drive control library, and the vehicle state data is processed according to the generation method of the first state data group to generate a first identification data group; that is, the drive control library is analyzed and constructed in advance, and each drive control library is associated with a first identification data group, and the drive control library can be retrieved through the first identification data group; the specific retrieval operation (matching) can be achieved by calculating the similarity between the first state data group and the first identification data group, and when the similarity is greater than or equal to a preset similarity threshold (any value between 0.80 and 1) and is the maximum, the first state data group and the first identification data group match; the similarity calculation method can adopt the cosine similarity calculation method.

[0040] In order to achieve the acquisition of vehicle status data in step one, in one embodiment, for the power battery, a pre-configured weight analysis table can be queried according to the remaining power of the power battery to determine the weight of the power battery; wherein the weight analysis table is pre-configured and constructed based on the principle that there is a positive relationship between the power of the power battery, the current weight of the power battery and the weight when it is empty, and the remaining power of the power battery in the table corresponds to the weight; wherein the weight includes: the empty weight and the weight determined according to the power.

[0041] For the trunk part, each seat space, each storage groove in the space between the main driver's seat and the co-driver's seat, the storage space in front of the co-driver's seat and other positions, pressure sensors can be configured at the corresponding positions, and then the corresponding weight (corresponding load) can be queried and determined according to the corresponding pressure-weight correspondence table configured; for example: the trunk can be equipped with a pressure sensor under the bottom plate of the box, and the seat can have a pressure sensor embedded inside the seat, etc.

[0042] In order to retrieve the control parameter set from the drive control library according to the current vehicle operating state, the specific retrieval steps are as follows:

[0043] Step 21: quantifying various data of the vehicle operating state and arranging them in a pre-configured order to form a second state data group;

[0044] For vehicle operating conditions with specific values ​​such as vehicle speed, acceleration, steering wheel angle, etc., the specific values ​​can be directly used as quantified data; for tire wear degree, road type, road condition, etc. without specific values, a quantization table pre-configured corresponding to the vehicle operating condition data of this type can be used to obtain quantized data after quantization processing; taking road type as an example, 01 represents asphalt road, 02 represents cement road, 03 represents cement road, etc.; taking road condition as an example, 101 represents dry road, 102 represents water accumulation on the road, 103 represents crushed ice on the road, 104 represents road temperature of -10-10 degrees, 105 represents road temperature of 10-30 degrees, etc.;

[0045] Step S22: matching the second state data group with the second identification data group corresponding to each control parameter set in the drive control library, and retrieving the control parameter set associated with the second identification data group matching the second state data group in the drive control library;

[0046] The drive control library is constructed in advance by professionals based on the analysis of the drive simulation data of the vehicle under different working conditions. The drive control part data is constructed into a control parameter set, and the specific working condition data is constructed into a second identification data group based on the construction method of the second state data group. The two are associated and stored in the drive control library; in addition, the matching method of the second state data group and the second identification data group is the same as that of the first state data group and the first identification data group, which will not be explained in detail here.

[0047] In order to obtain various data of the vehicle working state in step 2, in one embodiment, data such as vehicle speed, acceleration, steering wheel angle, etc. can be obtained by communicating with the vehicle central control computer to obtain its internal data;

[0048] The degree of tire wear can be determined by the following steps: according to the tire model, size, installation position on the vehicle and the model of the vehicle, the corresponding tire wear assessment database is retrieved; the driving record data of the vehicle after the tire is installed is retrieved, and features are extracted from the driving record data, and a wear analysis set is constructed according to the extracted feature values; the wear assessment result is determined according to the result of matching the wear analysis set with the retrieved set associated with each wear assessment result in the tire wear assessment database; the wear assessment result indicates the current degree of tire wear; wherein there are multiple tire wear assessment databases, which are constructed by professionals through analysis of specific test data under different tire models, sizes, installation positions on the vehicle and vehicle models, and one tire wear assessment database corresponds to one condition (the tire model, size, installation position on the vehicle and the vehicle model). The models are the same as a condition); the data in the wear analysis set include: a feature value indicating the number of left turns, a feature value indicating the number of right turns, a feature value indicating the mileage, a feature value indicating the difference between the time of the first driving after the tire is used and the current time, a feature value indicating the average vehicle speed, a feature value indicating the maximum vehicle speed, a feature value indicating the number of reversing times, a feature value indicating the total time of the direction deviating to the left when reversing, a feature value indicating the total time of the direction deviating to the right when reversing, etc.; in the tire wear assessment database, the call set is associated with the wear assessment results in a one-to-one correspondence, and the matching of the call set and the wear analysis set can be achieved by calculating the similarity between the two. When the similarity is the maximum and greater than a preset threshold, the two are matched; in addition, the call set is a data set constructed by the working condition data in the construction data used when constructing the tire wear assessment database according to the construction method of the wear analysis set.

[0049] In addition, in order to improve the accuracy of determining the degree of tire wear, when the degree of tire wear is detected during the use of the vehicle, the time and result of the detection result are obtained; the wear assessment result corresponding to the time of the detection result is retrieved from the tire wear assessment database; based on the time difference between the time of the detection result and the current moment, the detection result, and the wear assessment result, a correction value is retrieved from a pre-configured correction library, and the current wear assessment result is corrected with the correction value, wherein the wear assessment result and the detection result are both wear degrees expressed in percentages. When there are multiple actual wear detections, the pre-configured weight analysis library can be queried based on the detection time and the driving distance data corresponding to the detection, and the weight corresponding to each detection can be extracted, and the current wear assessment result can be corrected with the weight of the correction value determined corresponding to each detection.

[0050] For the road type and road condition, the vehicle's positioning data can be used to determine the road section where the vehicle is located from the road distribution map, and then retrieve the road type and road condition data associated with the road section. The vehicle only needs to upload the positioning data to the server, which will execute it, and then directly receive the road type and road condition data returned by the server.

[0051] In one embodiment, the DSP-based smart car driving method further includes:

[0052] Receive special operating condition control items and countdown time on the vehicle's driving path sent by the server;

[0053] Countdown is performed according to the countdown time. Before the countdown ends and before the control parameter set is determined, the current vehicle operating condition is first matched with the vehicle operating condition in the special operating condition control item. When the match is met, the control parameters corresponding to each controller are generated according to the control parameter set in the characteristic operating condition control item.

[0054] The steps for the server to generate special working condition control items and countdown time are as follows:

[0055] From the abnormal data repository, the data to be analyzed is selected based on the current location of the vehicle and the vehicle status data; the distance between the location in the selected data to be analyzed and the current location of the vehicle is within a preset distance threshold and the vehicle status data is consistent;

[0056] Constructing the vehicle operating state of the characteristic operating condition control item according to the vehicle operating state of the data to be analyzed;

[0057] According to the control parameter set and feedback effect data in the data to be analyzed, the corresponding parameter correction set is retrieved from the pre-configured correction library; the correction library is pre-configured, and the parameter correction set, control parameter set, and feedback effect data in the library are associated one by one;

[0058] Correcting each control parameter in the control parameter set according to the parameter correction set, and using the corrected control parameter set as the control parameter set of the special working condition control item; the correction is specifically: adding the data in the parameter correction set to the data at the corresponding position in the control parameter set to obtain data, and then replacing the data at the corresponding position in the control parameter set with the data;

[0059] According to the shortest distance between the positioning data corresponding to the data to be analyzed and the current positioning of the vehicle, a pre-configured distance-time comparison table is queried to determine the countdown time; wherein the countdown time corresponding to the shortest distance in the distance-time comparison table is greater than or equal to 2 times the shortest distance divided by the current vehicle speed.

[0060] The data stored in the abnormal data repository are abnormal data in the feedback data collected by the effect feedback terminal set on other vehicles, wherein the feedback data includes: vehicle operating status, current vehicle location, vehicle status data, control parameter set, feedback effect data (data monitored by the vibration monitoring sensor); when the vibration data monitored by the vibration monitoring sensor is greater than the preset vibration threshold, it can be judged as abnormal, that is, the feedback data is abnormal data. That is, the feedback terminal includes: a data acquisition module, a processing module, a vibration monitoring sensor and a communication module; the data acquisition module is used to communicate with the main controller to obtain the vehicle operating status, the current vehicle location, the vehicle status data, and the data corresponding to the control parameter set; the data acquisition module, the vibration monitoring sensor and the communication module are electrically connected to the processing module respectively. The communication module communicates with the server and is used to upload the collected data and feedback data.

[0061] The present invention also provides a DSP-based smart car driving system, which is applied to a smart car. The smart car includes: four drive motors and a main controller. The drive motors correspond to the wheels one by one and are transmission-connected. The main controller is communicatively connected with the DSP controllers of the drive motors. Figure 3 As shown, it includes: a first analysis module 1, a second analysis module 2 and a generation module 3; wherein the first analysis module 1 calls up a drive control library according to current vehicle status data; the second analysis module 2 calls up a control parameter set from the drive control library according to current vehicle operating conditions; the generation module 3 generates control parameters corresponding to each controller according to the control parameter set.

[0062] Wherein, the driving motor includes a wheel-side motor.

[0063] Wherein, the communication method between the main controller and the DSP controller of the drive motor includes: CAN bus communication.

[0064] The vehicle status data includes: the load at each pre-divided area location.

[0065] The vehicle operating status includes one or more combinations of vehicle speed, acceleration, steering wheel angle, tire wear, road surface type, and road conditions.

[0066] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A DSP-based smart car driving method, applied to a smart car, the smart car comprising: Four drive motors and a main controller, the drive motors correspond to the wheels one by one and are in transmission connection, and the main controller is in communication connection with the DSP controllers of each drive motor; characterized in that it includes: According to the current vehicle status data, the drive control library is retrieved; According to the current vehicle operating state, the control parameter set is retrieved from the drive control library; According to the control parameter set, the control parameters corresponding to each controller are generated.

2. The DSP-based smart car driving method according to claim 1, characterized in that: The drive motor includes a wheel-side motor.

3. The DSP-based smart car driving method according to claim 1, characterized in that: The communication method between the main controller and the DSP controller of the drive motor includes: CAN bus communication.

4. The DSP-based smart car driving method according to claim 1, characterized in that: The vehicle status data includes: the load at each pre-divided area location.

5. The DSP-based smart car driving method according to claim 1, characterized in that: The vehicle operating status includes one or more combinations of vehicle speed, acceleration, steering wheel angle, tire wear, road surface type, and road conditions.

6. A DSP-based smart car driving system, applied to a smart car, the smart car comprising: Four drive motors and a main controller, the drive motors correspond to the wheels one by one and are connected in transmission, and the main controller is communicatively connected with the DSP controllers of each drive motor; it is characterized by comprising: a first analysis module, a second analysis module and a generation module; wherein the first analysis module retrieves a drive control library according to current vehicle status data; the second analysis module retrieves a control parameter set from the drive control library according to current vehicle operating status; the generation module generates control parameters corresponding to each controller according to the control parameter set.

7. The DSP-based intelligent vehicle driving system according to claim 6 is characterized in that: The drive motor includes a wheel-side motor.

8. The DSP-based intelligent vehicle driving system according to claim 6 is characterized in that: The communication method between the main controller and the DSP controller of the drive motor includes: CAN bus communication.

9. The DSP-based intelligent vehicle driving system according to claim 6 is characterized in that: The vehicle status data includes: the load at each pre-divided area location.

10. The DSP-based intelligent vehicle driving system according to claim 6, characterized in that: The vehicle operating status includes one or more combinations of vehicle speed, acceleration, steering wheel angle, tire wear, road surface type, and road conditions.

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