Hybrid retarder road load prediction method

Abstract

This invention discloses a road load prediction method for hybrid power reducers. Based on the dynamic information collected from the vehicle under different road conditions, the method calculates the vehicle's power demand using vehicle speed, acceleration, and road gradient. The hybrid system distributes torque between the motor and engine drives with the highest power output efficiency as the driving boundary. Based on the proportion of road conditions in the total vehicle mileage, the method extends the cycle number under the corresponding torque to obtain the road load prediction result. This invention can be applied to road load prediction in the early stages of hybrid power reducer product development, providing input for the formulation of gear shaft load spectra.

Description

Technical Field

[0001] This invention belongs to the field of road load prediction technology for hybrid power reducers, and specifically relates to a method for predicting road loads of hybrid power reducers. Background Technology

[0002] In the P13 hybrid powertrain configuration, the engine power and electric motor power drive the vehicle in various operating modes, including direct motor drive, direct engine drive, and hybrid drive. The load spectrum borne by the hybrid reducer in different power transmission paths is subject to significant uncertainty due to factors such as the external characteristics of the power source, control strategy, and user usage scenarios.

[0003] For example, patent document CN102326186B discloses a method and apparatus for determining the load spectrum of a transmission in a motor vehicle, which introduces a method for determining the load spectrum of a traditional power transmission based on road data acquisition. This method has two limitations: firstly, it relies on actual vehicle data acquisition to determine the load spectrum, making it difficult to provide support in the early stages of project development; secondly, it cannot be used to guide the early development of the load spectrum for hybrid powertrains.

[0004] For example, patent document CN113392471A discloses a method, medium and device for compiling load spectrum of a hybrid electric vehicle reducer, which classifies based on power source mode and road conditions, mainly optimizing the post-processing based on actual road spectrum data, but does not involve the prediction of road load.

[0005] For example, patent document CN113255081B discloses a method for constructing the load spectrum of an electric vehicle reducer based on existing loads. This method mainly improves the load determination method based on existing accumulated data. However, with changes in the power system architecture, the applicability of the original data is questionable.

[0006] Therefore, it is necessary to develop a new method for predicting road loads on hybrid decelerators. Summary of the Invention

[0007] The purpose of this invention is to provide a road load prediction method for hybrid power reducers, which can quickly identify road load characteristics under different boundaries, so as to provide efficient guidance for design.

[0008] In a first aspect, the present invention provides a method for predicting road loads on a hybrid power reducer, comprising the following steps:

[0009] Step 1: Install the transmission 5 inside the vehicle 1;

[0010] Step 2: Drive the vehicle 1 on selected road conditions 1, 2, 3, 4, ..., K. During the driving process, record the vehicle speed υ, acceleration α, and road gradient θ in a time sequence using sensor 5.

[0011] Step 3: Based on the data of the vehicle platform or equivalent specifications on which the hybrid reducer is to be installed, and based on the vehicle's dynamic equation of motion FF... a -F r -F s =mα, which gives the wheel-side rotational speed n at any time t. wheel and torque demand T wheel Where: F is the wheel-side driving force of the whole vehicle, F a Converted to air resistance, F r For rolling resistance, F s For slope resistance; vehicle data includes drag coefficient C0, frontal area A, vehicle mass m, and rolling resistance coefficient f0;

[0012] Step 4: Based on the engine efficiency MAP diagram and motor efficiency MAP diagram matched with the hybrid reducer, and the design transmission ratio i at the engine end of the hybrid reducer... eng The design of the transmission ratio i at the motor end of the hybrid power reducer mot Query the hybrid power reducer engine-side design transmission rate η in the engine-side transmission efficiency Map. eng And query the hybrid reducer motor-end design transmission efficiency η in the motor-end transmission efficiency map. eng Using the highest overall hybrid power output efficiency as the system boundary, calculate the optimal engine drive speed n. eng Engine drive torque T eng Motor drive speed n mot and motor drive torque T mot The result should satisfy the wheel-side speed n calculated in step three. wheel and torque demand T wheel ;

[0013] Step 5: Perform the calculations from Step 4 on the data measured for road conditions 1, 2, 3, 4, ..., K respectively, to obtain the power source speed-torque spectra S1, S2, S3, S4, ..., S for road conditions 1, 2, 3, 4, ..., K. K Simultaneously, based on time t and vehicle speed υ, the test mileage l1, l2, l3, l4, ..., l for road conditions 1, 2, 3, 4, ..., K is calculated. K Based on time series interval Δt and engine driving speed n eng and motor drive speed n mot Calculate the engine driving revolutions c at any time t. eng and motor drive speed c mot ;

[0014] Step 6: Design target mileage L for the entire vehicle, and the percentage of road conditions 1, 2, 3, 4, ..., K in the total mileage of the vehicle, p1, p2, p3, p4, ..., p K According to formula N i =L*p i / l i Let i = 1, 2, 3, 4, ..., K. Then, we obtain the expansion coefficients N1, N2, N3, N4, ..., N of road conditions 1, 2, 3, 4, ..., K when expanded to the design target vehicle mileage L. K ;

[0015] Step 7: Calculate the engine drive speed c at any time t for road conditions 1, 2, 3, 4, ..., K obtained in Step 5. eng and motor drive speed c mot The corresponding expansion coefficients N1, N2, N3, N4, ..., N are multiplied by road condition 1, 2, 3, 4, ..., K. K The engine external drive speed C for road conditions 1, 2, 3, 4, ..., K is obtained. eng and the motor's external drive speed C mot ;

[0016] Step 8: Combine the road condition data 1, 2, 3, 4, ..., K obtained in Step 7 to obtain the total vehicle driving range design target L, including the engine drive torque T. eng Engine external drive speed C eng Motor drive torque T mot and the motor's external drive speed C mot The load data.

[0017] Optionally, in step one,

[0018] Sensor 5 is arranged on the central axis of the front left seat 2 and the front right seat 3 in the longitudinal direction of vehicle speed;

[0019] Sensor 5 is positioned at the extreme rearward position of the front seat 2 and the center line of the front envelope of the rear seat 4 in the transverse direction of the vehicle.

[0020] The transmission 5 is arranged on the upper surface of the vehicle floor in the vertical direction of the whole vehicle.

[0021] Optionally, in step two, the time series interval Δt is less than one-third of the vehicle CAN communication interval.

[0022] This invention has the following advantages: Based on the dynamic information collected from the vehicle under different road conditions, it calculates the vehicle's power demand using vehicle speed, acceleration, and road gradient. The hybrid system distributes torque between the motor and engine drives with the highest power output efficiency as the driving boundary. Based on the proportion of road conditions in the total vehicle mileage, the number of cycles under the corresponding torque is expanded to obtain the road load prediction result. This method can be applied to road load prediction in the early stages of hybrid reducer product development, providing input for the formulation of gear shaft load spectra. Attached Figure Description

[0023] Figure 1 This is the virtual design process for the load spectrum of the gear shaft system of the hybrid power reducer described in this invention;

[0024] Figure 2 This is a schematic diagram of the arrangement of the vehicle road condition acquisition sensors described in this invention;

[0025] In the picture: 1. The whole vehicle, 2. The left front seat, 3. The right front seat, 4. The front seats. Detailed Implementation

[0026] The present invention will now be described in detail with reference to the accompanying drawings.

[0027] like Figure 1 As shown in this embodiment, a road load prediction method for a hybrid power reducer includes the following steps:

[0028] Step 1: Arrange the transmission device 5 within the vehicle 1. Specifically, arrange sensor 5 along the central axis of the front left seat 2 and the front right seat 3 in the longitudinal direction of vehicle speed; arrange sensor 5 along the transverse direction of the vehicle at the position of the center line of the front seat 2's rearward movement limit and the front envelope of the rear seat 4; arrange the transmission device 5 vertically along the upper surface of the vehicle floor. See [link to relevant documentation]. Figure 2 .

[0029] Step 2: Drive the vehicle 1 on the selected road conditions 1, 2, 3, 4, ..., K. During the driving process, record the vehicle speed υ, acceleration α, and road slope θ in a time sequence through sensor 5. The time sequence interval Δt should be less than one-third of the vehicle CAN communication interval. The data recording format is shown in Table 1.

[0030] Table 1. Vehicle Data Recording Table under Road Conditions

[0031]

[0032] Step 3: Based on the data of the vehicle platform or equivalent specifications on which the hybrid reducer is to be installed, and based on the vehicle's dynamic equation of motion FF... a -F r -Fs =mα, which gives the wheel-side rotational speed n at any time t. wheel and torque demand T wheel Where: F is the wheel-side driving force of the whole vehicle, F a Converted to air resistance, F r For rolling resistance, F s For slope resistance; vehicle data includes drag coefficient C0, frontal area A, vehicle mass m, and rolling resistance coefficient f0;

[0033] Step four, based on the engine efficiency MAP and motor efficiency MAP matched with the hybrid power reducer...

[0034] Hybrid power reducer engine-side design transmission ratio i eng ,

[0035] The design transmission ratio i of the motor end of the hybrid reducer mot Query the hybrid power reducer engine-side design transmission rate η in the engine-side transmission efficiency Map. eng And query the hybrid reducer motor-end design transmission efficiency η in the motor-end transmission efficiency map. eng Using the highest overall hybrid power output efficiency as the system boundary, calculate the optimal engine drive speed n. eng Engine drive torque T eng Motor drive speed n mot and motor drive torque T mot The result should satisfy the wheel-side speed n calculated in step three. wheel and torque demand T wheel ;

[0036] Step 5: Perform the calculations from Step 4 on the data measured for road conditions 1, 2, 3, 4, ..., K respectively, to obtain the power source speed-torque spectra S1, S2, S3, S4, ..., S for road conditions 1, 2, 3, 4, ..., K. K Simultaneously, based on time t and vehicle speed υ, the test mileage l1, l2, l3, l4, ..., l for road conditions 1, 2, 3, 4, ..., K is calculated. K Based on time series interval Δt and engine driving speed n eng and motor drive speed n mot Calculate the engine driving revolutions c at any time t. eng and motor drive speed c mot ;

[0037] Step 6: Design target mileage L for the entire vehicle, and the percentage of road conditions 1, 2, 3, 4, ..., K in the total mileage of the vehicle, p1, p2, p3, p4, ..., p K According to formula Ni =L*p i / l i Let i = 1, 2, 3, 4, ..., K. Then, we obtain the expansion coefficients N1, N2, N3, N4, ..., N of road conditions 1, 2, 3, 4, ..., K when expanded to the design target vehicle mileage L. K ;

[0038] Step 7: Calculate the engine drive speed c at any time t for road conditions 1, 2, 3, 4, ..., K obtained in Step 5. eng and motor drive speed c mot The corresponding expansion coefficients N1, N2, N3, N4, ..., N are multiplied by road condition 1, 2, 3, 4, ..., K. K The engine external drive speed C for road conditions 1, 2, 3, 4, ..., K is obtained. eng and the motor's external drive speed C mot ;

[0039] Step 8: Combine the road condition data 1, 2, 3, 4, ..., K obtained in Step 7 to obtain the total vehicle driving range design target L, including the engine drive torque T. eng Engine external drive speed C eng Motor drive torque T mot and the motor's external drive speed C mot For the load data, please refer to Table 2.

[0040] Table 2 Road Working Condition Load Data

[0041]

[0042] This method collects vehicle dynamics information under road conditions for a specified vehicle model. This information reflects the user's driving habits and the characteristics of the roads during vehicle operation. Using this information as input, and based on the characteristics of the target hybrid power system, it performs virtual prediction of road loads, offering greater flexibility. By changing the parameters involved in the invention, it can quickly identify road load characteristics under different boundaries, efficiently providing guidance for design.

[0043] The above embodiments are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above embodiments. Any changes, modifications, substitutions, combinations, or simplifications made without departing from the spirit and principle of the present invention shall be considered equivalent substitutions and shall be included within the protection scope of the present invention.

Claims

1. A method for predicting road load on a hybrid power reducer, characterized in that, Includes the following steps: Step 1: Install the transmission 5 inside the vehicle 1; Step 2: Drive the vehicle 1 on selected road conditions 1, 2, 3, 4, ..., K. During the driving process, record the vehicle speed υ, acceleration α, and road gradient θ in a time sequence using sensor 5. Step 3: Based on the data of the vehicle platform or equivalent specifications on which the hybrid reducer is to be installed, and based on the vehicle's dynamic equation of motion FF... a -F r -F s =mα, which gives the wheel-side rotational speed n at any time t. wheel and torque demand T wheel Where: F is the wheel-side driving force of the whole vehicle, F a Converted to air resistance, F r For rolling resistance, F s For slope resistance; vehicle data includes drag coefficient C0, frontal area A, vehicle mass m, and rolling resistance coefficient f0; Step 4: Based on the engine efficiency MAP diagram and motor efficiency MAP diagram matched with the hybrid reducer, and the design transmission ratio i at the engine end of the hybrid reducer... eng The design of the transmission ratio i at the motor end of the hybrid power reducer mot Query the hybrid power reducer engine-side design transmission rate η in the engine-side transmission efficiency Map. eng And query the hybrid reducer motor-end design transmission efficiency η in the motor-end transmission efficiency map. eng Using the highest overall hybrid power output efficiency as the system boundary, calculate the optimal engine drive speed n. eng Engine drive torque T eng Motor drive speed n mot and motor drive torque T mot The result should satisfy the wheel-side speed n calculated in step three. wheel and torque demand T wheel ; Step 5: Perform the calculations from Step 4 on the data measured for road conditions 1, 2, 3, 4, ..., K respectively, to obtain the power source speed-torque spectra S1, S2, S3, S4, ..., S for road conditions 1, 2, 3, 4, ..., K. K Simultaneously, based on time t and vehicle speed υ, the test mileage l1, l2, l3, l4, ..., l for road conditions 1, 2, 3, 4, ..., K is calculated. K Based on time series interval Δt and engine driving speed n eng and motor drive speed n mot Calculate the engine driving revolutions c at any time t. eng and motor drive speed c mot ; Step 6: Design target mileage L for the entire vehicle, and the percentage of road conditions 1, 2, 3, 4, ..., K in the total mileage of the vehicle, p1, p2, p3, p4, ..., p K According to formula N i =L*p i / l i Let i = 1, 2, 3, 4, ..., K. Then, we obtain the expansion coefficients N1, N2, N3, N4, ..., N of road conditions 1, 2, 3, 4, ..., K when expanded to the design target vehicle mileage L. K ; Step 7: Calculate the engine drive speed c at any time t for road conditions 1, 2, 3, 4, ..., K obtained in Step 5. eng and motor drive speed c mot The corresponding expansion coefficients N1, N2, N3, N4, ..., N are multiplied by road condition 1, 2, 3, 4, ..., K. K The engine external drive speed C for road conditions 1, 2, 3, 4, ..., K is obtained. eng and the motor's external drive speed C mot ; Step 8: Combine the road condition data 1, 2, 3, 4, ..., K obtained in Step 7 to obtain the total vehicle driving range design target L, including the engine drive torque T. eng Engine external drive speed C eng Motor drive torque T mot and the motor's external drive speed C mot The load data.

2. The road load prediction method for hybrid power reducers according to claim 1, characterized in that: In step one, Sensor 5 is arranged on the central axis of the front left seat 2 and the front right seat 3 in the longitudinal direction of vehicle speed; Sensor 5 is positioned at the extreme rearward position of the front seat 2 and the center line of the front envelope of the rear seat 4 in the transverse direction of the vehicle. The transmission 5 is arranged on the upper surface of the vehicle floor in the vertical direction of the whole vehicle.

3. The road load prediction method for hybrid power reducers according to claim 1 or 2, characterized in that: In step two, the time series interval Δt is less than one-third of the vehicle CAN communication interval.

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