Method for online estimation of mass of new energy electric vehicle

Abstract

The invention relates to the technical field of new energy electric vehicles, in particular to an online mass estimation method for a new energy electric vehicle, which comprises a VCU (vehicle control unit), an MCU (microprogrammed control unit) and an ATM (automatic teller machine) gearbox control box, the ATM gearbox control box is provided with a slope signal sensor, the VCU is connected with the ATM gearbox control box, the MCU is connected with the VCU through a CAN (controller area network) bus, and the MCU is connected with the ATM gearbox control box through a CAN bus. The method specifically comprises the following steps that 1, whether conditions are met or not is judged, if yes, a VCU judges that the whole vehicle is in an anti-slope-sliding function enabling mode of 1, and 2, after an MCU receives an instruction enabling mode, the MCU enters a rotating speed control mode, the rotating speed of a motor is made to be 0, and the torque value of the motor is fed back in real time; after the conditions are detected to be met at the same time, the motor system exits from the anti-sliding slope, after the conditions are detected to be met at the same time, the motor system enters the anti-sliding slope again, and the execution is repeated for three times at most; the problems that a direct measurement method at the present stage is high in vehicle weight acquisition cost and complex in calibration, the subsequent use process needs regular calibration, and large-scale popularization cannot be achieved are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy electric vehicles, and in particular to a method for online estimating quality of new energy electric vehicles. Background Art

[0002] The gross mass of a vehicle refers to the weight of a vehicle when it is fully equipped and loaded as specified. According to relevant content in automobile theory, the gross mass of a vehicle will directly or indirectly affect the vehicle's power, economy, handling stability, braking, and passability. At the same time, according to relevant regulations on transportation management, the gross mass of a vehicle should be limited to a certain range. Therefore, it is necessary to estimate the vehicle's mass based on data collected in real time from the vehicle to avoid potential dangers caused by overloading.

[0003] At present, the method for obtaining vehicle weight indicators is direct measurement. The direct measurement method is to measure the vehicle weight through sensors. This method has the problems of high cost, complex calibration, the need for regular calibration during subsequent use, and inability to be promoted on a large scale. Summary of the invention

[0004] The present invention provides a method for online estimating the mass of a new energy electric vehicle. The method estimates the vehicle weight based on the longitudinal dynamics of the vehicle through the relationship between acceleration and force, thereby solving the problems of high cost, complex calibration, the need for regular calibration during subsequent use, and the inability to be promoted on a large scale in the current direct measurement method for obtaining the vehicle weight.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is: a method for online estimating the quality of a new energy electric vehicle, comprising a VCU vehicle controller, an MCU and an ATM gearbox control box, wherein the ATM gearbox control box is provided with a slope signal sensor, and the VCU vehicle controller and the ATM gearbox control box and MUC are connected via a CAN bus, specifically comprising the following steps:

[0006] Step S1, judging whether all the following conditions are met: A: the vehicle is in a ready state;

[0007] B: The vehicle strategic gear position is D / R;

[0008] C: The vehicle has no serious faults;

[0009] D: The battery system discharge power is greater than the calibrated value;

[0010] E: The available torque of the motor system is greater than the calibrated value;

[0011] F: Throttle opening = 0% and brake switch signal = 0 or brake pedal opening = 0%;

[0012] G: The vehicle strategy gear position = D and the motor speed is reverse rotation greater than the calibration value of 5rpm or the vehicle strategy gear position = R and the motor speed is forward rotation greater than the calibration value of 5rpm;

[0013] If all the above conditions are met, the VCU determines that the vehicle is in the anti-slope function enabled state = 1;

[0014] Step S2, when the anti-slip enable = 1, the MCU enters the speed control mode after receiving the enable command, quickly adjusts its own torque to make the motor speed = 0, and feeds back the motor torque value in real time; after 3 seconds, the motor system exits the anti-slip mode, and when it detects that the conditions in step 2 are met at the same time, it enters the anti-slip mode again, and the maximum number of repetitions is 3 times;

[0015] Step S3, when the vehicle is on a slope, the force formula of the whole vehicle is:

[0016]

[0017] Among them, m is the mass of the car, Ttq is the motor torque, ig is the transmission ratio, i0 is the main reduction ratio, η is the mechanical transmission efficiency, r is the wheel rolling radius, f is the rolling resistance friction coefficient, α is the slope angle, CD is the drag coefficient, A is the frontal area, u is the vehicle speed, du / dt is the acceleration, δ is the rotational mass conversion coefficient, g is the acceleration of gravity, Ft is the driving force of the car, m*g*f*cosa is the rolling friction resistance, m*g*sina is the slope resistance, is the air resistance, δ*m*du / dt is the acceleration resistance.

[0018] It is further defined that when the vehicle's anti-slope function is enabled and the motor speed is 0, that is, the entire vehicle is stationary on the slope, the vehicle speed is ua=0 at this time, so in the formula of step S3, the air resistance is 0, the entire vehicle remains stationary for 3 seconds, and the acceleration of the entire vehicle is also 0, so the acceleration resistance = 0, α is the slope angle, which is the slope sensor signal collected by the AMT in real time and will be sent to the VCU for reception in real time; f is the rolling resistance friction coefficient, which is provided by the tire manufacturer; Ttq is the motor torque, which the MCU will send to the VCU via the CAN bus in real time; ig is the transmission ratio, which the AMT will send to the VCU in real time according to the gear position of the entire vehicle; i0 is the main reduction ratio, which is a fixed value determined according to the vehicle configuration; η is the mechanical transmission efficiency, which can be set in the software as a calibration curve related to torque, or it can be set to a fixed empirical value of 0.96 after a rough calculation, and r is the wheel rolling radius.

[0019] With further limitation, it can be deduced that: m=Ttq*ig*i0*η{(gfcosa+sina)*r, where the calculated value of m starts from the motor speed = 0. One second later, the calculation of m is performed. The vehicle controller VCU calculates once every 10 milliseconds and will calculate many vehicle masses m0...m(n+1). VCU averages all valid calculation and estimation results, and the final average value of m is the estimated result of the final vehicle weight. Average value of m=(m1+m2+m3+m4+...mn) / n, where n is the number of valid calculation samples.

[0020] Further, in the estimated result data, VCU will subtract the largest value and the smallest value, respectively, to reduce the impact of outliers in the estimated results.

[0021] The beneficial effects of adopting the above technical solution are:

[0022] 1. The present invention estimates the mass of the entire vehicle by using the anti-slip working condition without increasing the cost, and the estimation result is highly accurate, fast and more efficient.

[0023] 2. The VCU vehicle controller determines whether the vehicle's anti-slope function is enabled, and the MCU executes stall control, quickly controlling the motor speed to 0 rpm to stop the vehicle on the slope. The AMT transmission controller has its own slope sensor to detect the slope value of the vehicle's driving route in real time. The AMT and VCU, as well as the VCU and MCU, exchange information in real time through the CAN bus. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a logical control schematic diagram of the present invention. DETAILED DESCRIPTION

[0025] The specific implementation methods of the present invention are further explained in detail below by describing the embodiments with reference to the accompanying drawings, with the aim of helping those skilled in the art to have a more complete, accurate and in-depth understanding of the concept and technical solution of the present invention and facilitating its implementation.

[0026] like Figure 1As shown, the present invention is a method for online estimating the quality of a new energy electric vehicle, comprising a VCU vehicle controller, an MCU and an ATM gearbox control box, wherein the ATM gearbox control box is provided with a slope signal sensor, the VCU vehicle controller and the ATM gearbox control box and the MUC are connected via a CAN bus to perform real-time information interaction, the VCU vehicle controller determines whether the vehicle is enabled to prevent the vehicle from sliding downhill, the MCU performs a stall control, and quickly controls the motor speed to reach 0rpm, so that the vehicle stops on the slope, and the AMT gearbox controller has a built-in slope sensor to detect the slope value on the vehicle's driving route in real time, specifically comprising the following steps: Step S1, determining whether all the following conditions are met:

[0027] A: The vehicle is in ready state;

[0028] B: The vehicle strategic gear position is D / R;

[0029] C: The vehicle has no serious faults;

[0030] D: The battery system discharge power is greater than the calibrated value;

[0031] E: The available torque of the motor system is greater than the calibrated value;

[0032] F: Throttle opening = 0% and brake switch signal = 0 or brake pedal opening = 0%;

[0033] G: The vehicle strategy gear position = D and the motor speed is reverse rotation greater than the calibration value of 5rpm or the vehicle strategy gear position = R and the motor speed is forward rotation greater than the calibration value of 5rpm;

[0034] If all the above conditions are met, the VCU determines that the vehicle is in the anti-slope function enabled state = 1;

[0035] Step S2, when the anti-slip enable = 1, the MCU enters the speed control mode after receiving the enable command, quickly adjusts its own torque to make the motor speed = 0, and feeds back the motor torque value in real time; after 3 seconds, the motor system exits the anti-slip mode, and when it detects that the conditions in step 2 are met at the same time, it enters the anti-slip mode again, and the maximum number of repetitions is 3 times;

[0036] Step S3, when the vehicle is on a slope, the force formula of the whole vehicle is:

[0037]

[0038] Among them, m is the mass of the car, Ttq is the motor torque, ig is the transmission ratio, i0 is the main reduction ratio, η is the mechanical transmission efficiency, r is the wheel rolling radius, f is the rolling resistance friction coefficient, α is the slope angle, CD is the drag coefficient, A is the frontal area, u is the vehicle speed, du / dt is the acceleration, δ is the rotational mass conversion coefficient, g is the acceleration of gravity, Ft is the driving force of the car, m*g*f*cosa is the rolling friction resistance, m*g*sina is the slope resistance, is the air resistance, δ*m*du / dt is the acceleration resistance.

[0039] When the vehicle's anti-slope function is enabled and the motor speed is 0, that is, the vehicle is stationary on the slope, the vehicle speed is ua=0 at this time, so in the formula of step S3, the air resistance is 0, the vehicle remains stationary for 3 seconds, and the acceleration of the vehicle is also 0, so the acceleration resistance = 0, α is the slope angle, which is the slope sensor signal collected by the AMT in real time and will be sent to the VCU in real time; f is the rolling resistance friction coefficient, which is provided by the tire manufacturer; Ttq is the motor torque, which the MCU will send to the VCU through the CAN bus in real time; ig is the transmission ratio, which the AMT will send to the VCU in real time according to the gear position of the vehicle; i0 is the main reduction ratio, which is a fixed value determined according to the vehicle configuration; η is the mechanical transmission efficiency, which can be set as a calibration curve related to torque in the software, and can also be set to a fixed empirical value of 0.96 after a rough calculation, and r is the wheel rolling radius.

[0040] Through the above steps, we can deduce m=Ttq*ig*i0*η{(gfcosa+sina)*r, where the calculated value of m starts from the motor speed=0. After 1 second, the calculation of m is performed. The vehicle controller VCU calculates once every 10 milliseconds and will calculate many vehicle masses m0...m(n+1). VCU averages all valid calculation and estimation results, and the final average value of m is the estimated result of the final vehicle weight. The average value of m=(m1+m2+m3+m4+...mn+1) / n, where n is the number of valid calculation samples. In the estimation result data, VCU will subtract the largest result value and the smallest result value, respectively, to reduce the impact of abnormal values ​​of the estimation result and improve the accuracy of the estimation. The maximum and minimum values ​​are regarded as invalid sample values.

[0041] The present invention is described above by way of example in conjunction with the accompanying drawings. Obviously, the specific implementation of the present invention is not limited to the above-mentioned method. As long as various non-substantial improvements are made using the method concept and technical solution of the present invention; or the above-mentioned concept and technical solution of the present invention are directly applied to other occasions without improvement, they are all within the protection scope of the present invention.

Claims

1. A method for online quality estimation of new energy electric vehicles, comprising a VCU vehicle controller, an MCU and an ATM gearbox control box, characterized in that: The ATM gearbox control box is provided with a slope signal sensor, and the VCU vehicle controller, the ATM gearbox control box and the MUC are connected via a CAN bus, specifically comprising the following steps: Step S1, determine whether all the following conditions are met: A: The vehicle is in ready state; B: The vehicle strategic gear position is D / R; C: The vehicle has no serious faults; D: The battery system discharge power is greater than the calibrated value; E: The available torque of the motor system is greater than the calibrated value; F: Throttle opening = 0% and brake switch signal = 0 or brake pedal opening = 0%; G: The vehicle strategy gear position = D and the motor speed is reverse rotation greater than the calibration value of 5rpm or the vehicle strategy gear position = R and the motor speed is forward rotation greater than the calibration value of 5rpm; If all the above conditions are met, the VCU determines that the vehicle is in the anti-slope function enabled state = 1; Step S2, when the anti-slip enable = 1, the MCU enters the speed control mode after receiving the enable command, quickly adjusts its own torque to make the motor speed = 0, and feeds back the motor torque value in real time; after 3 seconds, the motor system exits the anti-slip mode, and when it detects that the conditions in step 2 are met at the same time, it enters the anti-slip mode again, and the maximum number of repetitions is 3 times; Step S3, when the vehicle is on a slope, the force formula of the whole vehicle is: Among them, m is the mass of the car, Ttq is the motor torque, ig is the transmission ratio, i0 is the main reduction ratio, η is the mechanical transmission efficiency, r is the wheel rolling radius, f is the rolling resistance friction coefficient, α is the slope angle, CD is the drag coefficient, A is the frontal area, u is the vehicle speed, du / dt is the acceleration, δ is the rotational mass conversion coefficient, g is the acceleration of gravity, Ft is the driving force of the car, m*g*f*cosa is the rolling friction resistance, m*g*sina is the slope resistance, is the air resistance, δ*m*du / dt is the acceleration resistance.

2. The method for online estimating quality of a new energy electric vehicle according to claim 1, characterized in that: When the vehicle's anti-slope function is enabled and the motor speed is 0, that is, the vehicle is stationary on the slope, the vehicle speed is ua=0 at this time, so in the formula of step S3, the air resistance is 0, the vehicle remains stationary for 3 seconds, and the acceleration of the vehicle is also 0, so the acceleration resistance = 0, α is the slope angle, which is the slope sensor signal collected by the AMT in real time and will be sent to the VCU in real time; f is the rolling resistance friction coefficient, which is provided by the tire manufacturer; Ttq is the motor torque, which the MCU will send to the VCU through the CAN bus in real time; ig is the transmission ratio, which the AMT will send to the VCU in real time according to the gear position of the vehicle; i0 is the main reduction ratio, which is a fixed value determined according to the vehicle configuration; η is the mechanical transmission efficiency, which can be set as a calibration curve related to torque in the software, and can also be set to a fixed empirical value of 0.96 after a rough calculation, and r is the wheel rolling radius.

3. The method for online estimating quality of a new energy electric vehicle according to claim 2, characterized in that: It can be deduced that: m=Ttq*ig*i0*η{(gfcosa+sina)*r, where the calculated value of m starts from the motor speed = 0. One second later, the calculation of m is performed. The vehicle controller VCU calculates once every 10 milliseconds and will calculate many vehicle masses m0...m(n+1). VCU averages all valid calculation and estimation results, and the final average value of m is the estimated result of the final vehicle weight. Average value of m=(m1+m2+m3+m4+...mn+1) / n, where n is the number of valid calculation samples.

4. The method for online estimating quality of a new energy electric vehicle according to claim 3 is characterized by: In the estimated result data, VCU will subtract the largest result value and the smallest result value, respectively, to reduce the impact of abnormal values ​​in the estimated results.

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