An adaptive system and adaptive method for TAS sensor resolution

Abstract

The application discloses a kind of TAS sensor analytical adaptive system and adaptive method, the adaptive system includes battery, identification module, algorithm switching module, EEPROM module, CAN module and Power LDO;The adaptive method is for hella sensor and fareyo sensor utilizes two kinds of sensor signal characteristics, automatically calibrates, matches corresponding angle and torque analytical algorithm.The application solves the cost increase caused by hella sensor and fareyo sensor switching, when the production capacity of one kind of sensor is insufficient, the corresponding controller will be invalid and the problem of after-sales is not timely.The application reduces production cost, improves production efficiency, improves product utilization and reduces maintenance cost.

Description

TECHNICAL FIELD

[0001] The present application relates to a TAS sensor analysis adaptive system and adaptive method, belonging to the technical field of automotive electronic systems. BACKGROUND

[0002] In the prior art, the angle and torque signals of the whole vehicle steering system are processed by using sensors to process signals, and the calculated angle and torque signals are transmitted to actuators. The selection of sensor types is generally specified by the client to the supplier. The mainstream sensors on the market are Hella sensors and Faureo sensors. For steering gear development, a controller corresponds to a sensor signal (angle and torque) solving algorithm. Due to the production capacity of the sensor supplier, switching between Hella sensors and Faureo sensors is required, which results in the need for one-to-one correspondence between the controller and the sensor. This method will increase the cost of steering gear development, and additional costs are required to ensure the consistency of the sensor control during production and assembly. In addition, when the production capacity of one of the sensors is insufficient, the corresponding controller will be disabled, causing waste. For later customer replacement, there may be problems of delayed after-sales due to insufficient production capacity of the sensor. SUMMARY

[0003] The technical problem to be solved by the present application is to overcome the shortcomings of the prior art and provide a TAS sensor analysis adaptive system and adaptive method. For Hella sensors and Faureo sensors, the corresponding angle and torque analysis algorithms are automatically calibrated and matched by using the signal characteristics of the two types of sensors.

[0004] The present application adopts the following technical solution to solve the above technical problems: a TAS sensor analysis adaptive system, which automatically calibrates the signal characteristics of Hella sensors and Faureo sensors and matches the corresponding angle and torque analysis algorithms;

[0005] It includes a storage battery, an identification module, an algorithm switching module, an EEPROM module, a CAN module, and a Power LDO.

[0006] The identification module is used to distinguish the type of the TAS sensor used;

[0007] The algorithm switching module can adaptively switch the corresponding analysis algorithm according to the type of the TAS sensor. After the adaptive algorithm is adapted, a specific characteristic value is generated.

[0008] The EEPROM module stores the characteristic value generated by the algorithm switching module.

[0009] The battery is powered through a reverse prevention circuit and a Power LDO to the entire system.

[0010] The TAS sensor transmits the period and duty cycle signal of the sensor to the algorithm identification module for frequency sweeping to obtain characteristic values, and the angle and torque values are calculated through the algorithm switching module to generate characteristic values, and the CAN network interacts with the signals, the identification module is connected with the CAN network through a circuit and transmits the signals to the CAN network, and the characteristic values obtained by the algorithm switching module are sent to the EEPROM module through the CAN network, and the characteristic values are stored in the EEPROM module.

[0011] Further, the TAS sensor includes a Hella sensor and a Faure sensor,

[0012] The angle signal of the Hella sensor includes a P signal and an S signal, and the torque signal includes a T1 signal and a T2 signal; the corresponding signal frequencies are: the P signal frequency is 850Hz to 1150Hz, the S signal frequency is 178Hz to 222Hz, and the T1 / T2 signal frequency is 1700Hz to 2300Hz;

[0013] The angle signal of the Faure sensor includes an AS signal and an RS signal, and the torque signal includes a T1' signal and a T2' signal; the corresponding signal frequencies are: the AS / RS signal frequency is 900Hz to 1100Hz, and the T1' / T2' signal frequency is 1600Hz to 2400Hz;

[0014] The S signal in the Hella sensor signal and the RS signal in the Faure sensor signal are taken as the characteristic signals of the two sensors, and the frequencies of the S signal and the RS signal are taken as the characteristic points, and the S signal and the RS signal of the sensor are swept through the identification module to obtain the signal frequency, and the corresponding characteristic values are generated.

[0015] An adaptive method of an adaptive system of a TAS sensor analysis, comprising the following specific steps:

[0016] Step 1, the steering gear is assembled, powered by the battery, the identification module sweeps the main and auxiliary signals of the sensor to obtain the corresponding frequency information; according to the frequency information, the type of the TAS sensor is judged, and the signal is sent through the CAN network to generate characteristic values;

[0017] Step 2, input the characteristic values to the algorithm switching module, select the corresponding algorithm analysis channel according to the characteristic values, and after the algorithm analysis channel is confirmed, specific characteristic values will be generated again, and the flag bit is stored in the EEPROM module.

[0018] Further, in step 1, the CAN network sets ten signal periods for confirmation with 10ms as a signal period, takes 100ms as a judgment period, judges as Hella sensor when the frequency range is within 178Hz to 222Hz, and sends 0X0-Hella through the CAN network to generate the characteristic value 0_Hella; judges as Valeo sensor when the frequency range is within 900Hz to 1100Hz, and sends 0X1-Valeo through the CAN network to generate the characteristic value 1_Valeo; and sends 0X3-Invalid if the sensor is invalid.

[0019] Further, in step 2, the algorithm switching module includes two algorithm channels, which are defined as a first algorithm channel and a second algorithm channel respectively.

[0020] In the first algorithm channel, the P signal and the S signal of the Hella sensor are calculated through the vernier algorithm after signal initialization, the initial angle value is calculated, the final angle value is obtained according to the angle following, the T1 signal and the T2 signal of the Hella sensor are verified through the mutual verification of the T1 and T2 signals after protocol verification, the correctness of the signals is ensured, and then the torque value is calculated.

[0021] In the second algorithm channel, the AS signal and the RS signal of the Valeo sensor are calculated through the vernier algorithm after signal initialization, the initial angle value is calculated, the final angle value is obtained according to the angle following, the T1' signal and the T2' signal of the Hella sensor are verified through the mutual verification of the T1 and T2 signals after protocol verification, the correctness of the signals is ensured, and then the torque value is calculated.

[0022] Further, in step 2, the algorithm switching module includes the analysis algorithms of the Hella sensor and the Valeo sensor, and switches through the judgment characteristic value; the algorithm switching module reads the characteristic value information sent by the identification module, selects the first algorithm channel for analysis when the characteristic value is 0_Hella, analyzes the angle and torque of the Hella sensor, sends 0X0-SensorValid through the CAN network after the analysis is completed, and generates the characteristic value 0X00; selects the second algorithm channel for analysis when the characteristic value is 1_Valeo, analyzes the angle and torque of the Valeo sensor, sends 0X0-SensorValid through the CAN network after the analysis is completed, and generates the characteristic value 0X00; and sends 0X1-SensorInvalid and generates the characteristic value 0XFF when the sensor is in the state of not being analyzed, and stores the characteristic value in the EEPROM, so that whether the sensor is matched successfully can be judged through the characteristic value after the product is offline.

[0023] Compared with the prior art, the present application has the following advantages: the present application solves the problems of cost increase caused by switching of the Hella sensor and the Valeo sensor, failure of the corresponding controller when the production capacity of one of the sensors is insufficient, and untimely after-sales service. The present application reduces production cost, improves production efficiency, improves product utilization rate, and reduces maintenance cost. BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 It is a system architecture diagram of the present application.

[0025] Figure 2 It is a flowchart of the present application.

[0026] Figure 3 It is a working flowchart of the recognition module of the present application.

[0027] Figure 4 It is a working flowchart of the algorithm switching module of the present application.

[0028] Figure 5 It is a working flowchart of the first algorithm channel in the algorithm switching module of the present application.

[0029] Figure 6 It is a working flowchart of the second algorithm channel in the algorithm switching module of the present application. DETAILED DESCRIPTION

[0030] The technical solutions of the present application will be further described in detail below in combination with the drawings:

[0031] The present embodiment proposes an adaptive system for TAS sensor analysis, which automatically calibrates and matches the corresponding angles and torques for analysis algorithm through the signal characteristics of the Hella sensor and the Valeo sensor. The composition structure is as shown in Figure 1 The composition structure includes a storage battery, a recognition module, an algorithm switching module, an EEPROM module, a CAN module, and a Power LDO.

[0032] The recognition module is used to distinguish the type of the used TAS sensor;

[0033] The algorithm switching module can adaptively switch the corresponding analysis algorithm according to the type of the TAS sensor. After the adaptation of the analysis algorithm is completed, specific characteristic values are generated;

[0034] The EEPROM module stores the characteristic values generated by the algorithm switching module;

[0035] The storage battery is powered to the entire system through the Power LDO after passing through the anti-reverse circuit;

[0036] The TAS sensor transmits the period of the sensor and the duty cycle signal to the algorithm identification module to sweep the frequency, obtain the characteristic value, pass through the algorithm switching module, calculate the angle and torque value, generate the characteristic value, the CAN network interacts the signal, the identification module is connected with the CAN network through the circuit and transmits the signal to the CAN network, the characteristic value obtained by the algorithm switching module is sent to the EEPROM module through the CAN network, and the characteristic value is stored in the EEPROM module.

[0037] The TAS sensor includes a Hella sensor and a Faure sensor.

[0038] The angle signal of the Hella sensor includes a P signal and an S signal, and the torque signal includes a T1 signal and a T2 signal; the corresponding signal frequencies are as follows: the P signal frequency is 850Hz to 1150Hz, the S signal frequency is 178Hz to 222Hz, and the T1 / T2 signal frequency is 1700Hz to 2300Hz.

[0039] The angle signal of the Faure sensor includes an AS signal and an RS signal, and the torque signal includes a T1' signal and a T2' signal; the corresponding signal frequencies are as follows: the AS / RS signal frequency is 900Hz to 1100Hz, and the T1' / T2' signal frequency is 1600Hz to 2400Hz.

[0040] Therefore, the S signal in the Hella sensor signal and the RS signal in the Faure sensor signal are taken as the characteristic signals of the two sensors, the frequencies of the S signal and the RS signal are taken as the characteristic points, the S signal and the RS signal of the sensor are swept by the identification module, the signal frequency is obtained, and the corresponding characteristic value is generated.

[0041] The embodiment also provides an adaptive method of the adaptive system of the TAS sensor analysis, as shown in the figure, including the following specific steps: Figure 2

[0042] Step 1, the steering gear is assembled, the identification module sweeps the main and auxiliary signals of the sensor to obtain the corresponding frequency information by powering on through the storage battery; the type of the TAS sensor is judged according to the frequency information, and the signal is sent through the CAN network to generate the characteristic value, as shown in the figure. Figure 3 ​The CAN network is set to 10 ms as a signal cycle, ten signal cycles are set for confirmation, 100 ms is set as a judgment cycle, when the frequency range is within 178 Hz to 222 Hz, it is judged as a Hella sensor, 0X0-Hella is sent through the CAN network, the characteristic value 0_Hella is generated; when the frequency range is within 900 Hz to 1100 Hz, it is judged as a Valeo sensor, 0X1-Valeo is sent through the CAN network, the characteristic value 1_Valeo is generated; if the sensor fails, 0X3-Invalid is sent.

[0043] Step 2, the algorithm switching module includes two algorithm channels, which are defined as a first algorithm channel and a second algorithm channel; the characteristic value is input to the algorithm switching module, the algorithm switching module will select the corresponding algorithm analysis channel according to the characteristic value generated by the recognition module, after the algorithm analysis channel is confirmed, a specific characteristic value will be generated again, and a flag bit will be stored to the EEPROM module.

[0044] As shown in Figure 4 In the first algorithm channel, the P signal and the S signal of the Hella sensor are calculated after signal initialization and cursor algorithm, the initial angle value is calculated, the final angle value is obtained according to the angle following, the T1 signal and the T2 signal of the Hella sensor are first verified by the protocol, the correctness of the signals is ensured by mutual verification of the T1 and T2 signals, and then the torque value is calculated.

[0045] As shown in Figure 5 In the second algorithm channel, the AS signal and the RS signal of the Valeo sensor are calculated after signal initialization and cursor algorithm, the initial angle value is calculated, the final angle value is obtained according to the angle following, the T1' signal and the T2' signal of the Hella sensor are first verified by the protocol, the correctness of the signals is ensured by mutual verification of the T1 and T2 signals, and then the torque value is calculated.

[0046] The algorithm switching module includes analysis algorithms of two sensors of Hella sensor and Faureo sensor, and switches through judging characteristic values; the algorithm switching module reads characteristic value information sent by the identification module, when the characteristic value is 0_Hella, the algorithm switching module selects to analyze a first algorithm channel, and performs Hella sensor angle and torque analysis, after the analysis is completed, 0X0-SensorValid is sent through the CAN network, and characteristic value 0X00 is generated; when the characteristic value is 1_Valeo, the algorithm switching module selects to analyze a second algorithm channel, and performs Faureo sensor angle and torque analysis, after the analysis is completed, 0X0-SensorValid is sent through the CAN network, and characteristic value 0X00 is generated; when the sensor is in an unanalyzed state, 0X1-SensorInvalid is sent, characteristic value 0XFF is generated, and the characteristic value is stored in EEPROM, and after the product is offline, whether the sensor is matched successfully can be judged through the characteristic value.

[0047] The system and method provided in the embodiment can reduce production cost, the traditional method is that one sensor corresponds to one controller, when the sensor fails or the production capacity is insufficient, the corresponding controller will fail or stop, causing cost waste. The application enables the controller to correspond to different sensors, and when one of the sensors fails or the production capacity is insufficient, another sensor can still be used to match the controller.

[0048] Meanwhile, the production efficiency can be improved, the traditional method needs to increase the process or manual to ensure the consistency of the sensor and the controller, when the matching is not matched, rework is needed, resulting in low efficiency. The application realizes self-adaptive matching of the sensor and the controller, without increasing additional processes or manually confirming the consistency of the sensor and the controller, thereby improving the production efficiency.

[0049] The after-sales efficiency is improved, when the replacement part problem occurs in the traditional method, the after-sales personnel need to carry the corresponding sensor or controller to perform maintenance, but when the sensor or controller is short, the after-sales service will be delayed. The application improves the compatibility of the controller, and can avoid the above problems, thereby reducing the after-sales pressure.

[0050] The above shows and describes the basic principles, main features and advantages of the application. Those skilled in the art should understand that the application is not limited to the above specific embodiments, and the above specific embodiments and the description in the specification are only for further illustration of the principles of the application. Without departing from the spirit and scope of the application, various changes and improvements can be made to the application, and these changes and improvements all fall within the scope of the claimed application. The scope of the application claimed is defined by the claims and their equivalents.

Claims

1. A self-adapting system for TAS sensor resolution, characterized in that: Automatic calibration and matching of signal characteristics of Hella sensor and Faureo sensor and corresponding angle and torque analysis algorithm The battery, the identification module, the algorithm switching module, the EEPROM module, the CAN module and the Power LDO are included. The identification module is used for distinguishing the type of the TAS sensor used. The algorithm switching module is used for adaptively switching the corresponding analysis algorithm according to the type of the TAS sensor. The EEPROM module stores the specific characteristic value generated by the algorithm switching module. The battery is powered through the Power LDO after passing through the anti-reverse circuit. The TAS sensor transmits the period and duty cycle signals of the sensor to the identification module for frequency sweeping to generate a characteristic value. The TAS sensor includes a Hella sensor and a Faureo sensor. The angle signals of the Hella sensor include P signals and S signals, and the torque signals include T1 signals and T2 signals. The corresponding signal frequencies are as follows: the P signal frequency is 850-1150 Hz, the S signal frequency is 178-222 Hz, and the T1 / T2 signal frequency is 1700-2300 Hz. The angle signals of the Faureo sensor include AS signals and RS signals, and the torque signals include T1' signals and T2' signals.

2. An adaptive method of an adaptive system for resolving a TAS sensor according to claim 1, characterized in that: The corresponding signal frequencies are as follows: the AS / RS signal frequency is 900-1100 Hz, and the T1' / T2' signal frequency is 1600-2400 Hz. The S signal of the Hella sensor and the RS signal of the Faureo sensor are used as the characteristic signals of the two sensors, and the frequencies of the S signal and the RS signal are used as characteristic points. The following specific steps are included: Step 1: After the steering gear assembly is completed, the identification module sweeps the main and auxiliary signals of the sensor to obtain corresponding frequency information. Step 2: The characteristic value is input to the algorithm switching module, and the corresponding algorithm analysis channel is selected according to the characteristic value. The algorithm analysis channel will generate a specific characteristic value again after confirmation, and the flag bit will be stored in the EEPROM module.

3. The adaptive method of adaptive system of TAS sensor resolution according to claim 2, characterized in that: In step 1, the CAN network sets ten signal periods for confirmation with 10 ms as a signal period, and takes 100 ms as a judgment period, when the frequency range is within 178 Hz to 222 Hz, it is judged as a Hella sensor, and 0X0-Hella is sent through the CAN network to generate a characteristic value 0_Hella; when the frequency range is within 900 Hz to 1100 Hz, it is judged as a Valeo sensor, and 0X1-Valeo is sent through the CAN network to generate a characteristic value 1_Valeo; if the sensor is invalid, 0X3-Invalid is sent.

4. The adaptive method of adaptive system of TAS sensor resolution according to claim 2, characterized in that: In step 2, the algorithm switching module includes two algorithm channels, which are defined as a first algorithm channel and a second algorithm channel respectively; In the first algorithm channel, the P signal and the S signal of the Hella sensor are calculated through the vernier algorithm after signal initialization, and the initial angle value is calculated, and the final angle value is obtained according to the angle following, the T1 signal and the T2 signal of the Hella sensor are verified through the mutual verification of the T1 and T2 signals after protocol verification, to ensure the correctness of the signals, and then the torque value is calculated; In the second algorithm channel, the AS signal and the RS signal of the Valeo sensor are calculated through the vernier algorithm after signal initialization, and the initial angle value is calculated, and the final angle value is obtained according to the angle following, the T1' signal and the T2' signal of the Hella sensor are verified through the mutual verification of the T1 and T2 signals after protocol verification, to ensure the correctness of the signals, and then the torque value is calculated.

5. The adaptive method of adaptive system of TAS sensor resolution according to claim 4, characterized in that: In step 2, the algorithm switching module includes the analysis algorithms of the Hella sensor and the Valeo sensor, and switches through the judgment characteristic value; the algorithm switching module reads the characteristic value information sent by the identification module, when the characteristic value is 0_Hella, the algorithm switching module selects to analyze the first algorithm channel to analyze the angle and torque of the Hella sensor, and sends 0X0-SensorValid through the CAN network to generate a characteristic value 0X00 after analysis; when the characteristic value is 1_Valeo, the algorithm switching module selects to analyze the second algorithm channel to analyze the angle and torque of the Valeo sensor, and sends 0X0-SensorValid through the CAN network to generate a characteristic value 0X00 after analysis; when the sensor is in the state of not being analyzed, 0X1-SensorInvalid is sent to generate a characteristic value 0XFF, and the characteristic value is stored in the EEPROM, and after the product is offline, the characteristic value can be used to judge whether the sensor is matched successfully.

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