履带车辆自动变速系统智能控制策略及实验研究
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摘要
履带车辆是一种特殊的非公路车辆,所遇地形复杂多变,行驶阻力和附着系数频繁变化,驾驶员要根据地面阻力的变化不断地变换挡位和处理各种应急情况。由于履带车辆及其行驶环境的复杂性,目前履带车辆采用的自动换挡控制策略不能适应复杂多变的车内外行驶工况,在行驶路况与车况的建模、自动适应路形和路面状况变化的换挡控制策略以及履带车辆智能换挡仿真软件的开发等关键技术方面,还存在着很多问题。针对这些问题,本文进行了深入系统的理论和试验研究。
本文首先建立了履带车辆行驶工况的统计模型和车辆动力学模型。根据履带车辆路况变化的随机性,运用统计模拟方法,建立了车辆地面阻力系数、坡道阻力系数、转向阻力系数、地面附着系数等随机参量的统计模拟数学模型。采用数学模型与表格模型相结合的方法,根据液力变矩器与发动机的共同工作特性,建立了发动机、液力变矩器、行星变速箱和车体的动力学模型。
针对履带车辆行驶的地面形状(如坡道、弯道等)和路面状况(如山路、泥泞路面等)的特点,本文提出了模糊修正型控制和自适应模糊控制两种智能换挡控制策略。模糊修正型换挡控制策略将基本模糊决策模块与模糊修正模块相结合,基本模糊决策模块由动态三参数(油门开度、车速和加速度)换挡规律确定控制策略;模糊修正模块以油门开度变化率、制动力和转向半径三参数进行模糊换挡修正,根据反映驾驶员意图的参数自动调整挡位。在基本模糊控制策略基础上,建立了一个具有两级递阶结构的自适应模糊换挡控制系统,自适应模糊控制模块按照检测的车速和加速度对直线行驶阻力和附着力进行在线辨识,进而对车速和加速度量化因子进行自调整,可改善履带车辆在变化的路面条件下的换挡品质。
本文建立了履带车辆自动换挡控制系统的仿真模型,开发了自动换挡实验台的软硬件系统。为了验证已建立的智能换挡策略的正确性与可靠性,应用系统辨识与理论建模相结合的方法,建立了履带车辆智能换挡控制的仿真模型,仿真结果表明,所建立的智能换挡控制系统改善了履带车辆在各种工况下的换挡品质,有效避免了循环换挡现象的发生,从而验证了所设计的智能换挡策略的可行性。实验结果表明各种模糊控制策略可行,各种规则设置实现了预期的挡位,因此本文提出的各种换挡策略与方法有实用价值。
Tracked vehicle is a special non-highway vehicle. As the driving road situation of tracked vehicle is complex and changeful, running resistance changes greatly. As drivers have to dispose more and more information, current control strategy of automatic transmission of tracked vehicle cannot adapt to the complicated internal and external driving conditions. In order to decrease the frequency of gear shifting and alleviate the driver’s fatigue, new style tracked vehicle often adopt hydraulic mechanical transmission. After the investigations of intelligent shift strategy and adaptive fuzzy control technology of tracked vehicle drivetrain are implemented, a new technology of intelligent fuzzy control is presented to optimize manipulation according to road and vehicle conditions, and thus the cross-country maneuverability is improved.
Based on the randomicity of road condition variety, the statistic simulation maths models of random parameters are built using statistic simulation method, such as vehicle ground resistance coefficient, ramp resistance coefficient, turning resistance coefficient, ground adhesion coefficient. According to tracked vehicle steering parameters obtained by the sensors in automatic transmission, the driver manipulating intention and driving environment are concluded by fuzzy inferential method. It establishes foundation of intelligent shift system in complicated running conditions. The dynamic models of engine, hydraulic torque converter, planetary transmission and bodywork are built by means of maths model and table model. According to together working characteristics of engine and hydraulic torque converter, both of them not only have enough functions but also well matching. It establishes theoretic foundation of intelligent control and simulation system of automatic transmission.
According to the sum-up of drivers control experience, the primary principle of a fuzzy shift control of tracked vehicle under varying driving conditions is ascertained. Using the fuzzy control theory, an intelligent fuzzy shift control system composed of a basic fuzzy shift strategy and a fuzzy modification module is developed. A basic fuzzy shift strategy regards the conventional dynamic 3-parameter (vehicle speed, throttle position and vehicle acceleration) as input variables of fuzzy control and gear position as output variable. Because this shift strategy don’t adapt to the complicated driving conditions of tracked vehicle, this dissertation adds a fuzzy modification module. Therefore driver manipulating intention and driving environment are concluded. Based on a basic fuzzy shift strategy, a two-stage adaptive fuzzy control system and neural network control system for automatic transmission of tracked vehicle were established. According to the measured vehicle speed and acceleration, the adaptive fuzzy control module could identify linear running resistance and adhesive force of tracked vehicle and automatically regulated the fuzzy normalized factors. This system improves the shift quality of tracked vehicle under manifold driving conditions.
In order to validate the reliability of intelligent fuzzy shift strategy of tracked vehicle, based integrated methods both system discriminate and theoretics modeling, simulation models of intelligent shift of a tracked vehicle are established. The shifting parameters can be modified duly in system so as to provide referenced preliminary parameters. The vehicle performance and dynamic process of shifting in multifold shifting strategy are simulated. It can forecast the performance of automatic transmission and evaluate quality of shifting strategies. The purpose of the bench test of automatic transmission has been put forward and total project and test item of the bench test system have been described. So the feasibility of intelligent shift strategy built by this dissertation has been validated in the bench test.
本文首先建立了履带车辆行驶工况的统计模型和车辆动力学模型。根据履带车辆路况变化的随机性,运用统计模拟方法,建立了车辆地面阻力系数、坡道阻力系数、转向阻力系数、地面附着系数等随机参量的统计模拟数学模型。采用数学模型与表格模型相结合的方法,根据液力变矩器与发动机的共同工作特性,建立了发动机、液力变矩器、行星变速箱和车体的动力学模型。
针对履带车辆行驶的地面形状(如坡道、弯道等)和路面状况(如山路、泥泞路面等)的特点,本文提出了模糊修正型控制和自适应模糊控制两种智能换挡控制策略。模糊修正型换挡控制策略将基本模糊决策模块与模糊修正模块相结合,基本模糊决策模块由动态三参数(油门开度、车速和加速度)换挡规律确定控制策略;模糊修正模块以油门开度变化率、制动力和转向半径三参数进行模糊换挡修正,根据反映驾驶员意图的参数自动调整挡位。在基本模糊控制策略基础上,建立了一个具有两级递阶结构的自适应模糊换挡控制系统,自适应模糊控制模块按照检测的车速和加速度对直线行驶阻力和附着力进行在线辨识,进而对车速和加速度量化因子进行自调整,可改善履带车辆在变化的路面条件下的换挡品质。
本文建立了履带车辆自动换挡控制系统的仿真模型,开发了自动换挡实验台的软硬件系统。为了验证已建立的智能换挡策略的正确性与可靠性,应用系统辨识与理论建模相结合的方法,建立了履带车辆智能换挡控制的仿真模型,仿真结果表明,所建立的智能换挡控制系统改善了履带车辆在各种工况下的换挡品质,有效避免了循环换挡现象的发生,从而验证了所设计的智能换挡策略的可行性。实验结果表明各种模糊控制策略可行,各种规则设置实现了预期的挡位,因此本文提出的各种换挡策略与方法有实用价值。
Tracked vehicle is a special non-highway vehicle. As the driving road situation of tracked vehicle is complex and changeful, running resistance changes greatly. As drivers have to dispose more and more information, current control strategy of automatic transmission of tracked vehicle cannot adapt to the complicated internal and external driving conditions. In order to decrease the frequency of gear shifting and alleviate the driver’s fatigue, new style tracked vehicle often adopt hydraulic mechanical transmission. After the investigations of intelligent shift strategy and adaptive fuzzy control technology of tracked vehicle drivetrain are implemented, a new technology of intelligent fuzzy control is presented to optimize manipulation according to road and vehicle conditions, and thus the cross-country maneuverability is improved.
Based on the randomicity of road condition variety, the statistic simulation maths models of random parameters are built using statistic simulation method, such as vehicle ground resistance coefficient, ramp resistance coefficient, turning resistance coefficient, ground adhesion coefficient. According to tracked vehicle steering parameters obtained by the sensors in automatic transmission, the driver manipulating intention and driving environment are concluded by fuzzy inferential method. It establishes foundation of intelligent shift system in complicated running conditions. The dynamic models of engine, hydraulic torque converter, planetary transmission and bodywork are built by means of maths model and table model. According to together working characteristics of engine and hydraulic torque converter, both of them not only have enough functions but also well matching. It establishes theoretic foundation of intelligent control and simulation system of automatic transmission.
According to the sum-up of drivers control experience, the primary principle of a fuzzy shift control of tracked vehicle under varying driving conditions is ascertained. Using the fuzzy control theory, an intelligent fuzzy shift control system composed of a basic fuzzy shift strategy and a fuzzy modification module is developed. A basic fuzzy shift strategy regards the conventional dynamic 3-parameter (vehicle speed, throttle position and vehicle acceleration) as input variables of fuzzy control and gear position as output variable. Because this shift strategy don’t adapt to the complicated driving conditions of tracked vehicle, this dissertation adds a fuzzy modification module. Therefore driver manipulating intention and driving environment are concluded. Based on a basic fuzzy shift strategy, a two-stage adaptive fuzzy control system and neural network control system for automatic transmission of tracked vehicle were established. According to the measured vehicle speed and acceleration, the adaptive fuzzy control module could identify linear running resistance and adhesive force of tracked vehicle and automatically regulated the fuzzy normalized factors. This system improves the shift quality of tracked vehicle under manifold driving conditions.
In order to validate the reliability of intelligent fuzzy shift strategy of tracked vehicle, based integrated methods both system discriminate and theoretics modeling, simulation models of intelligent shift of a tracked vehicle are established. The shifting parameters can be modified duly in system so as to provide referenced preliminary parameters. The vehicle performance and dynamic process of shifting in multifold shifting strategy are simulated. It can forecast the performance of automatic transmission and evaluate quality of shifting strategies. The purpose of the bench test of automatic transmission has been put forward and total project and test item of the bench test system have been described. So the feasibility of intelligent shift strategy built by this dissertation has been validated in the bench test.
引文
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