Electric drive system oil quantity estimation method, oil quantity early warning strategy, electronic equipment and vehicle

Abstract

The invention discloses an electric drive system oil quantity estimation method, an oil quantity early warning strategy, electronic equipment and a vehicle, and the electric drive system oil quantity estimation method comprises the following steps: S1, constructing a motor temperature rise estimation model set which comprises a plurality of models used for estimating the motor temperature, each model is associated with a specific oil quantity calibration value and a specific oil temperature calibration value; s2, acquiring a current oil temperature estimation value, matching the current oil temperature estimation value with the oil temperature calibration value closest to the current oil temperature estimation value, calling all the models associated with the oil temperature calibration value, and calculating to obtain a plurality of estimation candidate values of the motor temperature; and S3, acquiring a current motor temperature actual value, matching the current motor temperature actual value with the estimation candidate value closest to the current motor temperature actual value, and determining the oil quantity calibration value associated with the model corresponding to the estimation candidate value as an oil quantity estimation value. The oil mass can be monitored, and an early warning signal can be sent out in time to remind a user that the oil mass of the electric drive system is abnormal.

Description

Technical Field

[0001] The present invention relates to a vehicle electric drive system, and in particular to an electric drive system oil quantity estimation method, an oil quantity early warning strategy, an electronic device and a vehicle. Background Art

[0002] As a core power component of new energy vehicles, the reliability of the electric drive system is crucial to vehicle safety. Currently, research and development focuses on oil-cooled all-in-one products, which primarily consist of three components: a motor, electronic control, and a reducer. The motor and reducer share a sealed chamber filled with oil, which is circulated by an electronic oil pump. The oil within the electric drive provides both lubrication and heat dissipation, significantly impacting its performance. Excessive oil levels increase churning resistance in the motor and reducer transmission components, reducing output torque. Excessive oil levels can lead to emptying of the oil pump, impairing motor and reducer lubrication and heat dissipation, and ultimately reducing output performance. Therefore, electric drive system design comprehensively considers factors such as lubrication, heat dissipation, and performance output to determine the optimal oil level. Due to the uncertainties in vehicle operating conditions, when electric drive products are installed in vehicles, there is a risk of oil leakage in the electric drive system in extreme cases. Failure to detect leaks in a timely manner can lead to power interruption. Summary of the Invention

[0003] In view of this, the purpose of the present invention is to provide an electric drive system oil level estimation method, an oil level warning strategy, an electronic device and a vehicle. The electric drive system oil level estimation method can monitor the oil level, and the oil level warning strategy can promptly issue a warning signal to prompt the user of abnormal oil level in the electric drive system.

[0004] A method for estimating the oil level of an electric drive system in the present invention comprises the following steps:

[0005] S1. Constructing a motor temperature rise estimation model set, wherein the motor temperature rise estimation model set includes multiple models for estimating motor temperature, each of the models being associated with a specific oil quantity calibration value and an oil temperature calibration value;

[0006] S2. Obtaining a current oil temperature estimate, matching it with the closest oil temperature calibration value, calling all the models associated with the oil temperature calibration value, and calculating a plurality of candidate motor temperature estimates;

[0007] S3. Obtain the current actual value of the motor temperature, match it with the estimated candidate value closest to it, and determine the oil quantity calibration value associated with the model corresponding to the estimated candidate value as the oil quantity estimated value.

[0008] Furthermore, the step S1 includes:

[0009] S101. Selecting a plurality of oil quantity calibration values ​​and a plurality of oil temperature calibration values ​​based on an oil quantity range and an oil temperature range of an electric drive system;

[0010] S102, obtaining a plurality of first preset operating conditions based on different combinations of oil quantity calibration values ​​and oil temperature calibration values;

[0011] S103 , conducting experiments under multiple first preset working conditions respectively, and obtaining multiple models associated with each of the first preset working conditions based on experimental test data.

[0012] Furthermore, step S103 includes:

[0013] S1031. Obtain multiple second preset operating conditions based on different combinations of motor losses and oil pump speeds;

[0014] S1032. Under one of the first preset operating conditions, test the motor temperature under each of the second preset operating conditions to obtain motor temperature test values ​​corresponding to different second preset operating conditions under the first preset operating condition;

[0015] S1033, setting the motor temperature test value as an output variable, setting the standardized motor loss and oil pump speed as input variables, performing regression analysis and fitting, and obtaining the model corresponding to the first preset working condition in step S1032;

[0016] S1034. Repeat steps S1032-S1033 until a plurality of models respectively associated with each of the first preset working conditions are obtained.

[0017] Further, the step S2 includes:

[0018] S201, obtaining a current oil temperature estimation value using a preset oil temperature estimation method;

[0019] S202, performing error calculations on the estimated oil temperature value and a plurality of calibrated oil temperature values, determining the calibrated oil temperature value closest to the estimated oil temperature value based on the error calculation results, and calling all the models associated with the calibrated oil temperature value;

[0020] S203 , obtaining motor loss and oil pump speed, and substituting them into all the models in step S202 respectively to obtain multiple candidate values ​​for motor temperature estimation.

[0021] Furthermore, the step S201 includes:

[0022] S2011, obtaining the oil pump current when the oil pump is started;

[0023] S2012: Calculate a current oil temperature estimate based on the oil pump current when the oil pump is started.

[0024] Furthermore, step S203 includes:

[0025] S2031. Obtaining a rotational speed and a torque of the motor, and calculating motor loss based on the rotational speed and the torque;

[0026] S2032, obtaining the oil pump speed;

[0027] S2033 , respectively substituting the motor loss and the oil pump speed into all the models in step S202 to obtain a plurality of estimated candidate values ​​of the motor temperature.

[0028] Further, the step S3 includes:

[0029] S301, collecting the current actual value of the motor temperature through the motor temperature sensor;

[0030] S302. Perform error calculations on the actual motor temperature value and the multiple estimated candidate values ​​in step S2 respectively, determine the estimated candidate value closest to the actual motor temperature value based on the error calculation results, and determine the oil quantity calibration value associated with the model corresponding to the estimated candidate value as the oil quantity estimated value.

[0031] An oil quantity early warning strategy in the present invention includes the following steps:

[0032] Obtaining an estimated oil quantity value based on the above-mentioned electric drive system oil quantity estimation method;

[0033] In response to the fuel quantity estimation value being not higher than a preset fuel quantity minimum threshold and lasting for not less than a preset time length, a warning signal is issued.

[0034] An electronic device in the present invention includes a processor and a memory for storing instructions executable by the processor, and the processor is configured to: execute the instructions to implement the above-mentioned electric drive system oil quantity estimation method or implement the above-mentioned oil quantity warning strategy.

[0035] A vehicle in the present invention includes the above-mentioned electronic device.

[0036] The beneficial effects of the present invention are:

[0037] (1) The present invention can estimate the motor temperature by dividing the oil quantity interval and the oil temperature interval, and combining the oil temperature estimation, motor loss calculation and motor temperature rise estimation model set. The difference between the actual motor temperature value collected by the motor temperature sensor and the motor estimated value is used to obtain a more accurate oil quantity estimation value, which is used to output the oil quantity signal. This realizes the estimation of the oil quantity of the electric drive system without adding an oil quantity sensor, and at the same time, by outputting the oil quantity signal to the motor controller, electric drive controller or vehicle controller, the oil quantity can be monitored.

[0038] (2) The present invention monitors the oil level by outputting an oil level signal to the electric drive control system or the vehicle control system. When the monitored oil level estimate Voil is not higher than the preset oil level minimum threshold Voil_limit and the duration is not less than the preset time length t, an early warning signal is promptly issued to inform the user of the abnormal oil level in the electric drive system, reminding the user in advance to carry out timely maintenance, reducing damage to the electric drive system components caused by the abnormal oil level, improving the reliability of the electric drive product, and also improving the safety of the vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to make the purpose, technical solutions and beneficial effects of the present invention more clear, the present invention provides the following drawings for illustration:

[0040] Figure 1 It is a structural schematic diagram of the oil cooling circulation system of the electric drive system of the present invention;

[0041] Figure 2 This is a flow chart of the method for estimating the oil level of an electric drive system according to the present invention;

[0042] Figure 3 This is a schematic block diagram of the process of performing oil quantity estimation when three oil quantity calibration values ​​and three oil temperature calibration values ​​are selected according to the present invention;

[0043] Figure 4 1 is a schematic block diagram of the process of performing oil quantity estimation when i oil quantity calibration values ​​and j oil temperature calibration values ​​are selected according to the present invention;

[0044] Figure 5 This is the relationship between the motor temperature and motor loss of a certain model of motor when the oil pump speed is 1000rpm;

[0045] Figure 6 This is the relationship between the motor temperature and the oil pump speed of a certain model of motor when the motor loss is 1kW;

[0046] Figure 7 This is a graph showing the relationship between the oil pump current and oil temperature for a certain type of motor;

[0047] Figure 8 This is the relationship diagram of the electromagnetic simulation motor efficiency of a certain model of motor;

[0048] Figure 9 A flow chart of the fuel quantity early warning strategy of the present invention;

[0049] Figure 10 This is a schematic flow chart of the oil quantity early warning strategy of the present invention. DETAILED DESCRIPTION

[0050] The technical solution of the present invention is described in detail below with reference to the accompanying drawings and embodiments.

[0051] Example 1:

[0052] like Figure 1 As shown, the oil cooling circulation system provides cooling and lubrication for the reducer and motor. It is divided into three circuits: the reducer cooling circuit, the motor stator cooling circuit, and the motor rotor cooling circuit. In the reducer cooling circuit, oil in the reducer cavity is sucked in by the oil pump. It flows along the oil path on the housing, through the filter and oil cooler, and then is divided into two paths to enter the motor stator and motor rotor. The motor stator cooling circuit flows through the motor housing into the oil spray rings on both sides of the stator. The oil spray rings spray the oil to the coils on both sides for cooling. The motor rotor cooling circuit flows through the reducer input shaft into the motor rotor shaft, and is sprayed out through the spray holes on the rotor to cool the stator coils and bearings.

[0053] The temperature rise of the motor is determined by the energy of heat generation and heat dissipation. Abnormal oil quantity leads to poor heat dissipation performance, which indirectly causes abnormal motor temperature rise. Therefore, by exploring the temperature rise law of the motor under different oil quantities and oil temperatures, the electric drive oil quantity can be estimated by estimating the deviation between the motor temperature rise and the actual motor temperature sensor signal.

[0054] like Figure 2-Figure 4 As shown, a method for estimating the oil level of an electric drive system in this embodiment includes the following steps:

[0055] S1. Constructing a motor temperature rise estimation model set, wherein the motor temperature rise estimation model set includes multiple models for estimating motor temperature, and each of the models is associated with a specific oil quantity calibration value and an oil temperature calibration value.

[0056] The sub-steps of step S1 are:

[0057] S101. Based on the oil quantity interval and oil temperature interval of the electric drive system, select i oil quantity calibration values ​​and j oil temperature calibration values; i and j are both positive integers. When selecting, i oil quantity calibration values ​​are selected along the oil quantity interval, and j oil temperature calibration values ​​are selected along the oil temperature interval. Preferably, the i oil quantity calibration values ​​can include the maximum value and the minimum value in the oil quantity interval, and the j oil temperature calibration values ​​can include the maximum value and the minimum value in the oil temperature interval.

[0058] Specifically, in this embodiment, i=3, j=3 is taken as an example for description.

[0059] The three oil volume calibration values ​​are V oil 1. V oil 2 and V oil 3, where V oil 1=V max 、V oil 2=V mid 、V oil 3=V min , V max Refers to the normal oil volume required in the electric drive system product parameters, V min Refers to the minimum oil volume allowed for the electric drive to work, V mid It means between V max and V min The specific value can be determined according to the actual heat dissipation and lubrication requirements of the electric drive system.

[0060] The three oil temperature calibration values ​​are T oil 1. T oil 2 and T oil 3, where T oil 1=Tl、T oil 2=Tz、T oil 3=Th, Tl represents low temperature, Tz represents normal temperature, and Th represents high temperature. The specific value can be defined according to the operating environment and technical requirements of the electric drive system.

[0061] Of course, i and j can also be other values. For example, when i is 5, V can be taken based on the above i=3. max With V mid The middle value between the two is taken as an oil calibration value, and then V mid With V min When j is 4, then based on the above j=3, a value between Tl and Th can be taken as the oil temperature calibration value.

[0062] S102 : Obtain a plurality of first preset operating conditions based on different combinations of oil quantity calibration values ​​and oil temperature calibration values.

[0063] There are i*j combinations of i oil quantity calibration values ​​and j oil temperature calibration values, and thus i*j first preset operating conditions can be obtained.

[0064] Specifically, in this embodiment, i=3, j=3 is taken as an example for description.

[0065] 3 oil volume calibration values ​​V oil 1. V oil 2 and V oil 3 respectively with 3 oil temperature calibration values ​​T oil 1. T oil 2 and Toil 3, there are 9 combinations in total, so 9 first preset working conditions can be obtained.

[0066] S103: Conduct tests under multiple first preset working conditions, and obtain multiple models associated with each of the first preset working conditions based on the test data. In this step, the test refers to a bench test, but may also be a simulation or other test method.

[0067] The sub-steps of step S103 are:

[0068] S1031. Obtain multiple second preset operating conditions based on different combinations of motor losses and oil pump speeds.

[0069] S1032. Under one of the first preset operating conditions, test the motor temperature under each of the second preset operating conditions to obtain motor temperature test values ​​corresponding to different second preset operating conditions under the first preset operating condition;

[0070] S1033, setting the motor temperature test value as an output variable, setting the standardized motor loss and oil pump speed as input variables, performing regression analysis and fitting, and obtaining the model corresponding to the first preset working condition in step S1032;

[0071] S1034. Repeat steps S1032-S1033 until a plurality of models respectively associated with each of the first preset working conditions are obtained.

[0072] The principle and process of obtaining the model are explained in detail below.

[0073] Based on the fixed oil temperature and oil volume boundary, the motor temperature rise law under the same oil pump speed and different motor losses is investigated and obtained as follows: Figure 5 The relationship diagram between motor temperature and motor loss shown in the figure performs linear fitting on the test data of motor temperature and motor loss at the same oil pump speed. The linear relationship between motor temperature and loss is established and is positively correlated.

[0074] Based on the fixed oil temperature and oil volume boundary, the motor temperature rise law under different oil pump speeds and the same motor loss is investigated and obtained as follows: Figure 6 The relationship diagram between motor temperature and oil pump speed shown in the figure performs linear fitting on the test data of motor temperature and oil pump speed under the same motor loss. The quadratic relationship between motor temperature and oil pump speed is established, and the correlation is negative.

[0075] Based on different oil pump speeds n1, n2, n3, n4, n5, and different motor losses P loss 1. P loss 2. P loss 3. Ploss 4. P loss 5, the motor temperature rise test data, through the main effect and interactive response results analysis, the motor loss P loss The main effect of oil pump speed n is significant, and there is an interaction between the two factors of oil pump speed and motor loss.

[0076] Since the magnitudes of motor temperature, motor loss, and oil pump speed vary greatly, in order to improve the accuracy of the model, the input variables oil pump speed and motor loss are standardized according to the following formula:

[0077] x1=(nn min ) / (n max -n min );

[0078] x2=(P loss -P loss_min ) / (P loss_max -P loss_min ).

[0079] Where x1 is the normalized oil pump speed, n is the original data value of the oil pump speed, and n min is the minimum value of the original data of the oil pump speed, n max is the maximum value of the original data of the oil pump speed;

[0080] x2 is the normalized motor loss, P loss is the original data value of motor loss, P loss_min is the minimum value of the original data of motor loss, P loss_max It is the maximum value of the raw data of motor loss.

[0081] The above standardization adopts Min-Max normalization, which is used to linearly scale the data to [0, 1].

[0082] Perform regression analysis and fitting on the standardized input variables x1 and x2 and the motor temperature test results to obtain the regression model:

[0083]

[0084] Where a, b, c, d, h, and g are fitting coefficients, x1 is the normalized oil pump speed, x2 is the normalized motor loss, and T m is the motor temperature.

[0085] From the above, we can see that when the oil temperature and oil volume are constant, the motor temperature can be estimated by combining the motor loss, oil pump speed and the above model.

[0086] By fixing the oil temperature and oil volume of the first preset working condition, and then performing bench testing, the motor temperature test values ​​under different second preset working conditions under the first preset working condition are measured. The motor temperature test value is set as the output variable, and the standardized motor loss and oil pump speed are set as the input variables. Regression analysis and fitting are performed to obtain the model corresponding to the first preset working condition. Repeating this operation can obtain different models corresponding to different first preset working conditions, which can be expressed as:

[0087]

[0088] The subscripts i and j in the formula are used to distinguish i oil quantity calibration values ​​and j oil temperature calibration values, a ij 、b ij 、c ij d ij 、h ij 、g ij are the fitting coefficients of different models. These models together constitute the motor temperature rise estimation model set.

[0089] For example, the combination of 3 oil quantity calibration values ​​and 3 oil temperature calibration values ​​can obtain 9 first preset working conditions. loss 1. P loss 2. P loss 3. P loss 4. P loss 5 and the combination of different oil pump speeds n1, n2, n3, n4, and n5 can obtain 25 second preset working conditions.

[0090] First, when the oil volume is calibrated to V oil 1 and the oil temperature calibration value is T oil 1, the bench test was carried out in 25 second preset working conditions respectively, and 25 motor temperature test values ​​were obtained. The motor temperature test value was set as the output variable, and the standardized motor loss and oil pump speed were set as the input variables. The regression analysis fitting was carried out and the oil volume calibration value was V oil 1 and the oil temperature calibration value is T oil Model under working condition 1:

[0091]

[0092] Then, under the operating conditions of the oil volume calibration value Voil2 and the oil temperature calibration value Toil1, bench tests were performed under 25 second preset operating conditions to obtain 25 motor temperature test values. The motor temperature test values ​​were set as output variables, and the standardized motor loss and oil pump speed were set as input variables. Regression analysis and fitting were performed to obtain the model under the operating conditions of the oil volume calibration value Voil2 and the oil temperature calibration value Toil1:

[0093]

[0094] Similarly, we get the model: T m31 =f 31 (P loss , n), T m12 =f 12 (P loss , n), T m22 =f 22 (P loss , n), T m32 =f 32 (P loss , n), T m13 =f 13 (P loss , n), T m23 =f 23 (P loss , n), T m33 =f 33 (P loss , n), these 9 models together constitute the motor temperature rise estimation model set.

[0095] S2. Get the current oil temperature estimate T oil , matching the oil temperature calibration value closest to it, calling all the models associated with the oil temperature calibration value, and calculating and obtaining multiple candidate values ​​for motor temperature estimation.

[0096] The sub-steps of step S2 are:

[0097] S201. Obtain a current oil temperature estimation value using a preset oil temperature estimation method.

[0098] There are many different oil temperature estimation methods in the prior art. In this embodiment, the method adopted is to obtain the oil pump current when the oil pump is started, and calculate the current oil temperature estimation value based on the oil pump current when the oil pump is started.

[0099] The oil pump strategy is obtained through bench test calibration. When the motor is not working, the oil pump runs at a constant initial speed n0. The relationship between oil temperature and oil pump current can be used to estimate the oil temperature. Figure 7 When the oil pump speed is constant, the oil pump current and oil temperature have a linear relationship and are negatively correlated. Therefore, the oil temperature can be estimated by the oil pump current when the oil pump is started. The oil temperature estimation formula is:

[0100] T oil =k×EOP_Current+m;

[0101] Where, T oil is the estimated value of oil temperature, EOP_Current is the oil pump current when the oil pump is started, and k and m are fitting coefficients.

[0102] According to the motor working mode and oil pump speed, when the motor working mode is high voltage standby and the oil pump speed is n0, the oil temperature estimation formula is combined with the current oil pump current EOP_Current to calculate the oil temperature estimation value T oil .

[0103] S202 , performing error calculations on the oil temperature estimation value and several oil temperature calibration values, determining the oil temperature calibration value closest to the oil temperature estimation value based on the error calculation results, and calling all the models associated with the oil temperature calibration value.

[0104] For example, the three oil temperature calibration values ​​are T oil 1. T oil 2 and T oil 3, where T oil 1=T1、T oil 2=Tz、T oil 3=Th, the estimated oil temperature T oil Calculate the absolute value of the difference with the three oil temperature calibration values ​​and then take the minimum value.

[0105] If min(|T oil -T oil 1|,|T oil -T oil 2|,|T oil -T oil 3|)=|T oil -T oil 1|,

[0106] Then the oil temperature calibration value is T oil 1 All the models associated with: T m11 =f 11 (P loss , n), T m21 =f 21 (P loss , n), T m31 =f 21 (P loss , n), then proceed to step S203.

[0107] If min(|T oil -T oil 1|,|T oil -T oil 2|,|T oil -T oil 3|)=|T oil -T oil 2|,

[0108] Then the oil temperature calibration value is T oil 2 All the models associated with: T m12 =f 12 (P loss , n), T m22 =f 22 (P loss , n), T m32 =f 32 (P loss , n), then proceed to step S203.

[0109] If min(|T oil -T oil 1|,|T oil -T oil 2|,|T oil -T oil 3|)=|T oil -T oil 3|,

[0110] Then the oil temperature calibration value is T oil 3 All the models associated with: T m13 =f 13 (P loss , n), T m23 =f 23 (P loss , n), T m33 =f 33 (P loss , n), then proceed to step S203.

[0111] S203 , obtaining motor loss and oil pump speed, and substituting them into all the models in step S202 respectively to obtain multiple candidate values ​​for motor temperature estimation.

[0112] The sub-steps of step S203 are:

[0113] S2031. Obtain the speed and torque of the motor, and calculate the motor loss based on the speed and torque.

[0114] Based on the electromagnetic simulation of the motor, we can get Figure 8 The efficiency data of the motor at different speeds and torques is shown in the figure. The motor loss at different motor speeds and torques can be calculated using the following motor loss calculation formula:

[0115]

[0116] Where, P loss is the motor loss, T is the motor torque, N is the motor speed, and η is the motor efficiency.

[0117] After collecting the motor's speed and torque through internal or external sensors, the motor loss calculation formula is substituted to calculate the motor loss. Collecting the motor's speed and torque through internal or external sensors is a prior art technique, and its principles will not be elaborated here.

[0118] S2032: Obtain the oil pump speed. Specifically, the oil pump speed may be acquired through a speed sensor or a Hall effect sensor. Using a speed sensor or a Hall effect sensor is conventional technology, and its principles are not described in detail here.

[0119] S2033 , respectively substituting the motor loss and the oil pump speed into all the models in step S202 to obtain a plurality of estimated candidate values ​​of the motor temperature.

[0120] For example, if the oil temperature calibration value is T in step S202 oil 1 All the models associated with: T m11 =f 11 (P loss , n), T m21 =f 21 (P loss , n), T m31 =f 21 (P loss , n), then substitute the motor loss and oil pump speed into these three models, and then get the estimated candidate values ​​T of the three motor temperatures m11 、T m21 、T m31 .

[0121] If the oil temperature calibration value is T in step S202, oil 2 All the models associated with: T m12 =f 12 (P loss , n), T m22 =f 22 (P loss , n), T m32 =f 32 (P loss , n), then substitute the motor loss and oil pump speed into these three models, and then get the estimated candidate values ​​T of the three motor temperatures m12 、T m22 、T m32 .

[0122] If the oil temperature calibration value is T in step S202, oil 3 All the models associated with: T m13 =f 13 (P loss , n), T m23=f 23 (P loss , n), T m33 =f 33 (P loss , n), then substitute the motor loss and oil pump speed into these three models, and then get the estimated candidate values ​​T of the three motor temperatures m13 、T m23 、T m33 .

[0123] S3. Get the current actual value of the motor temperature T m , matching the closest estimated candidate value, and determining the oil quantity calibration value associated with the model corresponding to the estimated candidate value as the oil quantity estimated value V oil .

[0124] The step S3 comprises:

[0125] S301, collecting the current actual value of the motor temperature T through the motor temperature sensor m ; Collect the actual motor temperature value T through the motor temperature sensor m This is prior art and its principle will not be described in detail here.

[0126] S302, the actual value of the motor temperature T m Perform error calculations with the multiple estimated candidate values ​​in step S2, determine the estimated candidate value closest to the actual value of the motor temperature based on the error calculation results, and determine the oil quantity calibration value associated with the model corresponding to the estimated candidate value as the oil quantity estimated value V oil .

[0127] For example, if three estimated candidate values ​​T of the motor temperature are obtained in step S203 m11 、T m21 、T m31 , the three estimated candidate values ​​are compared with the actual value of the motor temperature T m Make a comparison, calculate the absolute value of the difference and then take the minimum value:

[0128] If min(|T m -T m11 |,|T m -T m21 |,|T m -T m31 |)=|T m -T m11 |,

[0129] The estimated oil volume V oil =V oil 1=V max

[0130] If min(|T m -T m11 |,|T m -T m21 |,|T m -T m31 |)=|T m -T m21 |,

[0131] The estimated oil volume V oil =V oil 2=V mid ;

[0132] If min(|T m -T m11 |,|T m -T m21 |,|T m -T m31 |)=|T m -T m31 |,

[0133] The estimated oil volume V oil =V oil 3=V min .

[0134] Similarly, if the estimated candidate values ​​T of the three motor temperatures are obtained in step S203 m12 、T m22 、T m32 , compare the three estimated candidate values ​​with the actual value of the collected motor temperature, calculate the absolute value of the difference and then take the minimum value:

[0135] If min(|T m -T m12 |,|T m -T m22 |,|T m -T m32 |)=|T m -T m12 |,

[0136] The estimated oil volume V oil =V oil 1=V max

[0137] If min(|T m -T m12 |,|T m -T m22 |,|T m -T m32 |)=|T m -T m22 |,

[0138] The estimated oil volume V oil =V oil 2=V mid ;

[0139] If min(|T m -T m12 |,|T m -T m22 |,|T m -T m32 |)=|T m -T m32 |,

[0140] The estimated oil volume V oil =V oil 3=V min

[0141] Similarly, if the estimated candidate values ​​T of the three motor temperatures are obtained in step S203 m13 、T m23 、T m33 , compare the three estimated candidate values ​​with the actual value of the collected motor temperature, calculate the absolute value of the difference and then take the minimum value:

[0142] If min(|T m -T m13 |,|T m -T m23 |,|T m -T m33 |)=|T m -T m13 |,

[0143] The estimated oil volume V oil =V oil 1=V max

[0144] If min(|T m -T m13 |,|T m -T m23 |,|T m -T m33 |)=|T m -T m23 |,

[0145] The estimated oil volume V oil =V oil 2=V mid ;

[0146] If min(|T m -T m13 |,|Tm -T m23 |,|T m -T m33 |)=|T m -T m33 |,

[0147] The estimated oil volume V oil =V oil 3=V min .

[0148] This electric drive system oil level estimation method estimates motor temperature by dividing oil level intervals into oil temperature intervals and oil temperature intervals, and combining a set of oil temperature estimation, motor loss calculation, and motor temperature rise estimation models. The difference between the actual motor temperature value collected by the motor temperature sensor and the estimated motor temperature value is used to obtain a relatively accurate oil level estimate, which is then used to output an oil level signal. This method allows for oil level estimation in the electric drive system without the need for additional oil level sensors. Furthermore, by outputting the oil level signal to the motor controller, electric drive controller, or vehicle controller, oil level monitoring can be implemented.

[0149] Example 2:

[0150] In this embodiment, a fuel quantity warning strategy is Figure 9 and Figure 10 As shown, the following steps are included:

[0151] Obtain an estimated fuel quantity value based on the fuel quantity estimation method for the electric drive system in Example 1;

[0152] In response to the fuel quantity estimation value being not higher than a preset fuel quantity minimum threshold and lasting for not less than a preset time length, a warning signal is issued.

[0153] By outputting an oil level signal to the electric drive control system or the vehicle control system to monitor the oil level, when the monitored oil level estimate Voil is not higher than the preset oil level minimum threshold Voil_limit and the duration is not less than the preset time length t, a warning signal is promptly issued to inform the user of the abnormal oil level in the electric drive system, reminding the user in advance to carry out timely maintenance, reducing damage to the electric drive system components caused by abnormal oil level, improving the reliability of the electric drive product, and also improving the safety of the vehicle.

[0154] Example 3:

[0155] In this embodiment, an electronic device includes a processor and a memory for storing instructions executable by the processor. The processor is configured to execute the instructions to implement the electric drive system fuel level estimation method of Example 1 or the fuel level warning strategy of Example 2. The electronic device may be, but is not limited to, a motor controller, an electric drive controller, a vehicle controller, or an onboard monitoring and diagnostic device.

[0156] Example 4:

[0157] A vehicle in this embodiment includes the electronic device in embodiment 3. The vehicle may be, but is not limited to, a pure electric vehicle, a hybrid vehicle, an extended-range electric vehicle, a new energy vehicle, or the like.

[0158] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the purpose and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for estimating the oil level of an electric drive system, characterized in that: The following steps are involved: S1. Constructing a motor temperature rise estimation model set, wherein the motor temperature rise estimation model set includes multiple models for estimating motor temperature, each of the models being associated with a specific oil quantity calibration value and an oil temperature calibration value; S2. Obtaining a current oil temperature estimate, matching it with the closest oil temperature calibration value, calling all the models associated with the oil temperature calibration value, and calculating a plurality of candidate motor temperature estimates; S3. Obtain the current actual value of the motor temperature, match it with the estimated candidate value closest to it, and determine the oil quantity calibration value associated with the model corresponding to the estimated candidate value as the oil quantity estimated value.

2. The method for estimating the oil level of an electric drive system according to claim 1, characterized in that: The step S1 comprises: S101. Selecting a plurality of oil quantity calibration values ​​and a plurality of oil temperature calibration values ​​based on an oil quantity range and an oil temperature range of an electric drive system; S102, obtaining a plurality of first preset operating conditions based on different combinations of oil quantity calibration values ​​and oil temperature calibration values; S103 , conducting experiments under multiple first preset working conditions respectively, and obtaining multiple models associated with each of the first preset working conditions based on experimental test data.

3. The method for estimating the oil level of an electric drive system according to claim 2, characterized in that: The step S103 includes: S1031. Obtain multiple second preset operating conditions based on different combinations of motor losses and oil pump speeds; S1032. Under one of the first preset operating conditions, test the motor temperature under each of the second preset operating conditions to obtain motor temperature test values ​​corresponding to different second preset operating conditions under the first preset operating condition; S1033, setting the motor temperature test value as an output variable, setting the standardized motor loss and oil pump speed as input variables, performing regression analysis and fitting, and obtaining the model corresponding to the first preset working condition in step S1032; S1034. Repeat steps S1032-S1033 until a plurality of models respectively associated with the first preset working conditions are obtained.

4. The method for estimating the oil level of an electric drive system according to claim 2 or 3, characterized in that: The step S2 comprises: S201, obtaining a current oil temperature estimation value using a preset oil temperature estimation method; S202, performing error calculations on the estimated oil temperature value and a plurality of calibrated oil temperature values, determining the calibrated oil temperature value closest to the estimated oil temperature value based on the error calculation results, and calling all the models associated with the calibrated oil temperature value; S203 , obtaining motor loss and oil pump speed, and substituting them into all the models in step S202 respectively to obtain multiple candidate values ​​for motor temperature estimation.

5. The method for estimating oil quantity of an electric drive system according to claim 4, characterized in that: The step S201 includes: S2011, obtaining the oil pump current when the oil pump is started; S2012: Calculate a current oil temperature estimate based on the oil pump current when the oil pump is started.

6. The method for estimating oil quantity of an electric drive system according to claim 4, characterized in that: The step S203 includes: S2031. Obtaining a rotational speed and a torque of the motor, and calculating motor loss based on the rotational speed and the torque; S2032, obtaining the oil pump speed; S2033 , respectively substituting the motor loss and the oil pump speed into all the models in step S202 to obtain a plurality of estimated candidate values ​​of the motor temperature.

7. The method for estimating oil quantity of an electric drive system according to claim 6, characterized in that: The step S3 comprises: S301, collecting the current actual value of the motor temperature through the motor temperature sensor; S302. Perform error calculations on the actual motor temperature value and the multiple estimated candidate values ​​in step S2 respectively, determine the estimated candidate value closest to the actual motor temperature value based on the error calculation results, and determine the oil quantity calibration value associated with the model corresponding to the estimated candidate value as the oil quantity estimated value.

8. A fuel quantity early warning strategy, characterized in that: The following steps are involved: Obtaining an estimated oil level value based on the oil level estimation method for an electric drive system according to any one of claims 1 to 7; In response to the fuel quantity estimation value being not higher than a preset fuel quantity minimum threshold and lasting for not less than a preset time length, a warning signal is issued.

9. An electronic device, characterized in that: It includes a processor and a memory for storing instructions executable by the processor, and the processor is configured to: execute the instructions to implement the oil quantity estimation method of the electric drive system as described in any one of claims 1 to 7 or implement the oil quantity warning strategy as described in claim 8.

10. A vehicle, characterized in that: Comprising the electronic device as claimed in claim 9.

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