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A new energy vehicle ride comfort optimization method based on big data

A technology of new energy vehicles and optimization methods, which is applied in the field of ride comfort optimization of new energy vehicles based on big data, and can solve problems such as vehicle ride comfort deterioration.

Active Publication Date: 2021-03-02
JIANGLING MOTORS
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The present invention proposes a method for optimizing the ride comfort of new energy vehicles based on big data. The server detects the ride comfort status of the vehicle, adjusts the parameters of torque compensation, and achieves the purpose of continuously optimizing the ride comfort of the vehicle

Method used

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  • A new energy vehicle ride comfort optimization method based on big data
  • A new energy vehicle ride comfort optimization method based on big data
  • A new energy vehicle ride comfort optimization method based on big data

Examples

Experimental program
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Embodiment 1

[0021] see figure 1 , the present invention is based on big data new energy vehicle ride comfort optimization method, through the following steps, to achieve continuous optimization of vehicle ride comfort:

[0022] Step 1. T-BOX (vehicle terminal) detects the vehicle motor torque, motor speed, and vehicle speed signals, and uploads the collected vehicle data to the big data server;

[0023] Step 2, the big data server analyzes the long-term running data of the vehicle, and obtains the vibration condition of the vehicle by calculating the frequency and amplitude of the motor vibration ( Figure 4 Shown is the vibration data of the whole vehicle) whether it is caused by the change of the clearance of the transmission system. For the fluctuation caused by the vehicle factor, the motor torque compensation parameter is adjusted by using the motor anti-shake compensation algorithm (ASD);

[0024] Step 3, T-BOX updates the anti-shake parameters through the vehicle network (receives...

Embodiment 2

[0026] see figure 1 , figure 2 , image 3 The ride comfort optimization method for new energy vehicles based on big data in this embodiment is different from Embodiment 1 in that the motor anti-shake compensation algorithm (ASD) reversely compensates the torque of the motor when the vehicle shakes To reduce the jitter value of the speed, by calculating the difference between the actual speed and the target speed, multiplying it by the compensation coefficient Kp to obtain the actual motor torque that needs to be compensated, adjust the motor torque compensation parameters; and analyze the compensated vehicle speed fluctuation data , if there is optimization, the current jitter compensation parameters will be sent to T-BOX; usually the compensation coefficient Kp is fixed, when the gap of the vehicle transmission system changes, this Kp parameter may not meet the needs of vehicle jitter compensation At this time, this parameter is optimized through the analysis of big data, ...

Embodiment 3

[0028] see figure 1 , figure 2 , image 3 , Figure 4 . The big data-based ride comfort optimization method for new energy vehicles in this embodiment is different from Embodiment 1 in that: the cloud server performs data processing through the motor speed uploaded by T-BOX and the torque signal requested by the VCU. If the speed fluctuation of the lower motor exceeds a calibrated amount, it can be judged that the vehicle is in a situation where the vibration is too large. It is necessary to adjust the torque compensation parameters and increase the torque compensation:

[0029] When the jitter occurs, there will be a basic anti-shake function between the VCU and the MCU (microprocessor). Data analysis, the T-BOX forwards the anti-shake parameter adjustment data to the internal anti-shake algorithm of the MCU, and adjusts the compensation gain of the torque;

[0030] In the motor anti-shake compensation algorithm, the compensation of the motor torque is obtained through ...

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Abstract

The present invention relates to a new energy vehicle ride comfort optimization method based on big data, including step 1, T-BOX detects vehicle motor torque, motor speed, and vehicle speed signals, and uploads the collected vehicle data to a big data server ; Step 2, the big data server analyzes the long-term running data of the vehicle, and obtains whether the vibration of the vehicle is caused by the change of the transmission system gap by calculating the frequency and amplitude of the motor vibration. For the fluctuation caused by the vehicle factor, the motor anti-shake is used The compensation algorithm adjusts the motor torque compensation parameters; Step 3, T‑BOX updates the anti-shake parameters through the vehicle network to adjust the motor compensation torque. The invention solves the problem of poor vehicle ride comfort caused by changes in the mechanical clearance of the power system when the new energy vehicle is driven by a motor, and adjusts the parameters of torque compensation through the detection of the vehicle ride comfort state by the cloud server to achieve vehicle ride comfort. Sexual continuous optimization.

Description

technical field [0001] The invention relates to a vehicle ride comfort optimization method for a new energy vehicle. Based on the Internet of Vehicles technology, the shake condition of the motor speed is detected, the torque of the motor is compensated, the shake of the motor speed is reduced, and the ride comfort of the vehicle is optimized. Background technique [0002] At present, with the serious problem of environmental pollution, the state has issued a series of policies to encourage the development and development of new energy vehicle technology. During the use of new energy vehicles, due to temperature changes or long-term mechanical wear, the mechanical properties of the transmission system will be damaged. As the gap becomes larger, the original torque compensation value cannot adapt to the current vehicle condition, and the ride comfort of the vehicle will deteriorate. In view of the progress of various detection technologies and information transmission technolo...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): B60L15/20
CPCB60L15/20B60L2240/12B60L2240/421B60L2240/423Y02T10/72
Inventor 胡松华刘伟东
Owner JIANGLING MOTORS
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