分布式驱动电动汽车自适应巡航控制策略研究

胡胜利; 张缓缓; 江忠顺; 常笑宇

doi:10.13433/j.cnki.1003-8728.20220211

分布式驱动电动汽车自适应巡航控制策略研究

doi: 10.13433/j.cnki.1003-8728.20220211

1.
上海工程技术大学机械与汽车工程学院，上海　201620

基金项目: 国家自然科学基金项目（51705306）

详细信息

作者简介:
胡胜利，硕士，m010120487@sues.edu.cn

通讯作者:
张缓缓，副教授，硕士生导师，zhanghh@sues.edu.cn

中图分类号: U469.72
计量
- 文章访问数: 79
- HTML全文浏览量: 34
- PDF下载量: 14
- 被引次数: 0
出版历程
- 收稿日期: 2021-12-05
- 网络出版日期: 2024-03-08
- 刊出日期: 2024-02-01

Research on Adaptive Cruise Control Strategy of Distributed Driving Electric Vehicles

1.
School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science , Shanghai 201620, China

摘要

摘要: 以分布式驱动汽车为研究对象，针对多目标协同的自适应巡航问题，应用非线性可变车头时距模型，对坡道、弯道工况设计了间距补偿策略，提高实际车间距离信号的准确性；综合考虑车辆行驶安全性，舒适性，节能性，设计了基于模型预测控制（Model predictive control，MPC）算法、分层控制的自适应巡航控制（Adaptive cruise control， ACC）系统。基于变步长离散化的方法改进ACC系统多目标协同上层控制算法，在保证较长预测时域的基础上提高系统的精确性和实时性。下层控制器中建立逆驱动系统模型、逆制动系统模型，制动/驱动切换逻辑，以车辆整体驱动效率最优为目标设计了期望力矩分配策略。在CarSim/Simulink搭建仿真环境验证了所设计策略的有效性。
- 自适应巡航 /
- 模型预测控制 /
- 间距补偿策略 /
- 分布式驱动电动汽车 /
- 力矩分配
Abstract: Taking distributed driven vehicle as research object, aiming at the adaptive cruise problem of multi-objective coordination, the nonlinear variable time headway model was applied to design the spacing compensation strategy for the rampway and curve road conditions, which improved the accuracy of the distance signal of the actual workspace. The adaptive cruise control (ACC) system based on model predictive control (MPC) algorithm and layered control was designed considering vehicle safety, comfort and energy saving. The variable step size discretization method is used to improve ACC system multi-objective cooperative upper controller, enhancing the accuracy and real-time performance of system. In the lower controller, the inverse drive system model, the inverse brake system model, and the brake switch/drive logic were established, and the expected torque distribution strategy was designed to optimize the overall driving efficiency of the vehicle. The simulation environment was built in CarSim/Simulink to verify the effectiveness of the designed strategy.
- adaptive cruise /
- model predictive control /
- spacing compensation strategy /
- distributed driven vehicle /
- torque distribution

HTML全文

图 1 系统结构图

Figure 1. System structure

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图 2 车辆上下坡模型

Figure 2. Vehicle up and down slope model

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图 3 坡道距离对比

Figure 3. Contrasting distance of ramps

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图 4 直线行驶下驱动效率对比图

Figure 4. Linear drive efficiency comparison

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图 5 弯道行驶驱动效率对比图

Figure 5. Bend drive efficiency comparison

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图 6 直流无刷电机模型

Figure 6. Brushless DC motor model

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图 7 直线道路启停跟随工况仿真结果

Figure 7. Simulation results of straight road stop & go following condition

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图 8 坡道稳定跟随工况仿真结果

Figure 8. Simulation results of stable following condition of a ramp

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图 9 车辆行驶路径图

Figure 9. Vehicle drive route

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图 10 弯道稳定跟随工况仿真结果

Figure 10. Simulated curves of bend stable following condition

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表 1 电机控制系统参数

Table 1. Motor control system parameters

电机控制参数	数值
电机电阻$ R/\Omega $	0.125
电感$ L/{\mathrm{mH}} $	3.75
反电动势系$ {k_{\mathrm{e}}}/[{\text{V}} \cdot {{\text{(}}{\mathrm{r}} \cdot \min {\text{)}}^{ - 1}}] $	0.25
PID参数$ {K_{\mathrm{P}}}/{K_{\mathrm{I}}}/{K_{\mathrm{D}}} $	200/30/2
电流反馈系数$ {k_{\rm{l}}} $	36
PWM装置延迟系数$ {k_{\mathrm{s}}} $	0.4
增益系数$k$	2

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表 2 车辆的基本参数

Table 2. Vehicle's basic parameters

参数	数值
簧下质量${m_{\rm{u}}}$	90 kg
簧上质量${m_{\rm{s}}}$	1650 kg
外形尺寸$L \times W \times H$	3 048 mm×1 880 mm×1 480 mm
质心到前轴的距离$a$	1400 mm
质心到后轴的距离$b$	1650 mm
前/后轮轮距$B$	1625 mm
轮心高度$c$	350 mm
质心高度${h_{\mathrm{g}}}$	530 mm
有效滚动半$r$	353 mm
内部轮胎型号	225/60 R18

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