Road Profile(道路概况)研究综述
Road Profile 道路概况 - To further enhance passengers’ comfort, a decentralized LPV H2 controller for the semi-active suspension system is proposed, minimizing the effect of the road profile variations. [1] This drug class also has a broad profile of activity against bacteria associated with community-based pneumonia, including atypical agents. [2] The responses of a vehicle have been analysed under the Indian average random road profile (ISO8608) against the conventional passive suspension system. [3] The predominant role of a piezoelectric harvester system in Vibration Energy Harvesting (VEH) is to gather vibrations energy caused by road profile disturbances. [4] The value of the threshold depends on the vibrations induced to the sprung mass by the road profile. [5] The time responses of cushion contact force, head vertical and fore-aft motion are studied for two road profiles—random and bump. [6] It is considered that the road profile consists of a finite number of the sum of sinusoidal signals with unknown amplitudes, phases and frequencies. [7] 2 eV in FWHM allowed us to observe the asymmetric broad profile of the electronic characteristic Kα and Kβ x rays together with the hypersatellite K^{h}α x rays around 6 keV. [8] This network uses road profile and the vehicle speed as inputs. [9] The significant factors of road profile and system dynamics including cornering stiffness, roll stiffness, roll damping coefficients, acceleration pedal and brake dynamics comparable to the real-world vehicle are neglected in research studies. [10] The calculated root mean square error RMSE and the relative error Ef between the measured and estimated profiles showed that the proposed approach can be used to accurately estimate road profiles. [11] The spring deforms to the road undulations, relieving the chassis from following the road profile. [12] Nevertheless, none of the models takes into account a road profile, i. [13] The sinusoidal road profile is set as the disturbance of this system. [14] Exemplary standard road profile excitations are also conducted to demonstrate the applicability of the designed system for frequency-domain testing of components in the vehicle suspension systems. [15] The dynamic H∞ observer is designed to minimize the effects of unknown disturbances (measurement noises and road profile) on the estimation errors by using an H∞ approach, while the nonlinearity coming from the damper model is satisfied a Lipschitz condition. [16] Since we obtained the suitable damping characteristics that met the requirements under random road profiles and bumpy roads, the realization of these characteristics will enable us to satisfy the driving requirements. [17] This paper considers the problem for designing a robust control design for Active Seat Suspension system being affected by a non-linear actuator and uneven road profile. [18] We equipped the simulator platform with: three actuators to render the road profile vibrations, an asphalt specimen attached to the rear tire to render the road adhesion, and a new virtual reality environment to render a part of the city of Vanves in France. [19] It was sought to recover a broad profile, beyond traditional conceptions, so that five dimensions of analysis were included, which are demographic, socioeconomic, academic, professional aspirations and the life project. [20] This work aims to perform kinematic and compliance analysis on comprehensive quarter car model of McPherson suspension system to validate its reliability with respect to various road profiles and development of control algorithm to control its stiffness. [21] By evaluating the performance at a random road profile, it is shown that both ride comfort and road holding (steering stability) can be enhanced by utilizing the fast-response MR damper. [22] A complete control system is needed to provide the desired suspension performance and characteristics such as passenger comfort, road handling, and suspension deflection, this control system performed using the MATLAB/SIMULINK and includes three parts: input signals (actuator force and road profile), Controller part, and the suspension system model. [23] In this article, a corresponding artificial neural network nonlinear active suspension controller has been designed and optimized for approximate road profiles, using simulation according to International Organization for Standardization 2631-5 and International Organization for Standardization 8608 standardizations. [24] In this paper, a reduced-order observer is designed using an unknown input decoupling approach to estimate the road profile and the state variables of vehicle suspension system. [25] The simulation results are in general accordance with expectations in the harvestable power interval versus the input excitation parameters, road profile rate, and piezoelectric properties. [26] Concept of symmetry covers physical link between road profile form, vehicle dynamic characteristics, and speed conjunction. [27] The road model used in the study has been modeled according to non-random road profile mathematical formulation considering periodical and discrete road profile cases. [28] Vehicle dynamics model in type of 1/4 is used for vibration analysis under the effect of random road profile with different grades. [29] Stress state of the details of suspension of a cargo vehicle during the movement on random road profile was simulated. [30] As the passive suspensions are most widely used in the automobiles, therefore this paper deals with the investigations of the suspension behavior at the different values of the road profile amplitude. [31] To fulfill these requirements, firstly, this paper introduces new topics, which is related to two Compact Road Profiler (CRP) to monitor the road roughness conditions including localized distresses. [32] Also, the simulation results with the road profile show that the proposed method is independent of the road profile. [33] In the analytical study, the acceleration response of the car was obtained, where the input was a road profile with an arbitrary pattern. [34] Then, the simultaneous estimation method of road profile and system state variables and the identification method of road level are studied. [35] To effectively realize control strategies, it is essential to foreknowledge the road profile and the suspension system’s internal state variables. [36] The nonlinear disturbance observer is proposed to asymptotically reject the external disturbances and overcome parametric uncertainties which exist in the suspension system such as road profiles, different passenger masses, and actuator dynamics. [37] For illustrative purposes, the coupled vibration problem of a regular truck traveling on a random road profile over a typical Brazilian bridge is analyzed. [38] The second one is the ability of the wheel to follow the road profile as closely as possible, which can be directly correlated with the amount of mechanical grip of the vehicle. [39] The driving and road profile are measured using accelerometer and gyroscope sensors. [40] Two long road profile tests conducted in kinematic mode are then analyzed to assess the capability of the approach. [41] Afterwards, an optimal solution is sought between the Pareto alternatives provided by the two road cases, in order for the tyre wear levels to be less affected under different road profiles. [42] Different road profiles are used to test the active suspension system response, such as a step input of 0. [43] The Chi-Square test was also performed in order to identify the relationship between accident severity and type of vehicle (in MVA and SVA) and the relationship between heavy vehicle accident severity and type of topography of road profile. [44] The controller is tested with Sinusoidal excitation then with ISO 8608 road profile. [45] Introduction Vibration suspension system is used in the automobiles to mitigate the excitations that can come from the travel over various road profiles. [46] Design/methodology/approachUnlike papers that consider simple vehicle models (quarter vehicle model or half car model) and/or simplified road profiles (harmonic excitation, for example) and/or perform a single-objective optimization and/or execute the dynamic analysis in the time domain, this paper presents an effective and fast methodology for the multi-objective optimization of the suspension system of a full-car model (including the driver seat) traveling on an irregular road profile, whose dynamic response is determined in the frequency domain, considerably reducing computational time. [47] The Matlab 2019a software is used to simulate the suspension models with bump road profiles as excitation disturbance. [48] The excitation signals collected from these road profiles are also employed in subsystem shaker rigs and virtual simulations that are gradually replacing physical complete vehicle test and verification. [49] After having obtained the optimum design solutions, the optimal solutions are simulated using IPG/CarMaker by assigning the road profiles on a 23 km long countryside road path. [50]为了进一步提高乘客的舒适度，提出了一种用于半主动悬架系统的分散式 LPV H2 控制器，以最大限度地减少道路轮廓变化的影响。 [1] 该类药物还具有广泛的抗社区性肺炎相关细菌的活性，包括非典型药物。 [2] 在印度平均随机道路剖面 (ISO8608) 下对传统被动悬架系统的车辆响应进行了分析。 [3] 压电收集器系统在振动能量收集 (VEH) 中的主要作用是收集由道路轮廓扰动引起的振动能量。 [4] 阈值的值取决于道路轮廓对簧载质量产生的振动。 [5] 研究了两种道路剖面——随机和颠簸的缓冲接触力、头部垂直和前后运动的时间响应。 [6] 认为道路轮廓由有限数量的具有未知幅度、相位和频率的正弦信号之和组成。 [7] FWHM 中的 2 eV 使我们能够观察到电子特征 Kα 和 Kβ x 射线的不对称宽轮廓以及 6 keV 附近的超卫星 K^{h}α x 射线。 [8] 该网络使用道路轮廓和车速作为输入。 [9] 在研究中忽略了与现实世界车辆相当的道路轮廓和系统动力学的重要因素，包括转弯刚度、侧倾刚度、侧倾阻尼系数、加速踏板和制动动力学。 [10] 计算的均方根误差 RMSE 和测量和估计轮廓之间的相对误差 Ef 表明，所提出的方法可用于准确估计道路轮廓。 [11] 弹簧会根据路面起伏变形，从而减轻底盘跟随路面轮廓的压力。 [12] 然而，没有一个模型考虑道路剖面，即。 [13] 正弦道路轮廓被设置为该系统的扰动。 [14] 还进行了示例性标准道路轮廓激励，以证明所设计系统在车辆悬架系统中的组件的频域测试中的适用性。 [15] 动态 H∞ 观测器旨在通过使用 H∞ 方法最小化未知干扰（测量噪声和道路轮廓）对估计误差的影响，而来自阻尼器模型的非线性满足 Lipschitz 条件。 [16] 由于我们获得了在随机道路剖面和颠簸路面下满足要求的合适阻尼特性，这些特性的实现将使我们能够满足驾驶要求。 [17] 本文考虑了为受非线性执行器和不平坦路面影响的主动式座椅悬架系统设计鲁棒控制设计的问题。 [18] 我们为模拟器平台配备了：三个执行器来渲染道路轮廓振动，一个附着在后轮胎上的沥青样品来渲染道路附着力，以及一个新的虚拟现实环境来渲染法国 Vanves 市的一部分。 [19] 它试图恢复一个广泛的形象，超越传统的概念，因此包括五个分析维度，即人口、社会经济、学术、职业抱负和生活项目。 [20] 本工作旨在对 McPherson 悬架系统的综合四分之一汽车模型进行运动学和合规性分析，以验证其在各种路况下的可靠性，并开发控制算法来控制其刚度。 [21] 通过评估随机路况下的性能，表明通过使用快速响应的 MR 阻尼器可以提高乘坐舒适性和抓地力（转向稳定性）。 [22] 需要一个完整的控制系统来提供所需的悬架性能和特性，例如乘客舒适度、道路操控性和悬架偏转，该控制系统使用 MATLAB/SIMULINK 执行，包括三个部分：输入信号（执行器力和道路轮廓），控制器部分，以及悬挂系统模型。 [23] 在本文中，根据国际标准化组织 2631-5 和国际标准化组织 8608 标准化，使用模拟，针对近似道路轮廓设计和优化了相应的人工神经网络非线性主动悬架控制器。 [24] 在本文中，使用未知输入解耦方法设计了一个降阶观测器来估计道路轮廓和车辆悬架系统的状态变量。 [25] 模拟结果通常与可收获功率区间与输入激励参数、道路剖面速率和压电特性的预期一致。 [26] 对称概念涵盖了道路轮廓形式、车辆动态特性和速度结合之间的物理联系。 [27] 研究中使用的道路模型是根据考虑周期性和离散道路剖面情况的非随机道路剖面数学公式建模的。 [28] 采用1/4型车辆动力学模型，进行不同等级随机道路剖面作用下的振动分析。 [29] 模拟了货车在随机道路剖面运动过程中悬挂细节的应力状态。 [30] 由于被动悬架在汽车中的应用最为广泛，因此本文主要研究了不同路形幅值下的悬架性能。 [31] 为了满足这些要求，首先，本文介绍了与两个紧凑型道路剖面仪（CRP）相关的新主题，以监测包括局部故障在内的道路粗糙度条件。 [32] 此外，道路剖面的仿真结果表明，所提出的方法与道路剖面无关。 [33] 在分析研究中，获得了汽车的加速度响应，其中输入是具有任意模式的道路轮廓。 [34] 然后，研究了道路剖面与系统状态变量的同时估计方法和道路标高的识别方法。 [35] 为了有效地实现控制策略，必须预知道路轮廓和悬架系统的内部状态变量。 [36] 提出非线性扰动观测器以渐近抑制外部扰动并克服悬架系统中存在的参数不确定性，例如道路轮廓、不同乘客质量和执行器动力学。 [37] 出于说明目的，分析了一辆普通卡车在随机道路剖面上行驶在典型的巴西桥梁上的耦合振动问题。 [38] 第二个是车轮尽可能紧密地跟随道路轮廓的能力，这可以与车辆的机械抓地力直接相关。 [39] 使用加速度计和陀螺仪传感器测量驾驶和道路轮廓。 [40] 然后分析在运动学模式下进行的两个长路剖面测试，以评估方法的能力。 [41] 之后，在两种路况提供的帕累托备选方案之间寻求最优解，以减少不同路况下轮胎磨损程度的影响。 [42] 使用不同的道路剖面来测试主动悬架系统的响应，例如步输入为 0。 [43] 为了确定事故严重程度与车辆类型（在 MVA 和 SVA 中）之间的关系以及重型车辆事故严重程度与道路轮廓地形类型之间的关系，还进行了卡方检验。 [44] 控制器使用正弦激励然后使用 ISO 8608 道路剖面进行测试。 [45] 简介 振动悬架系统用于汽车中，以减轻可能来自各种道路剖面行驶的激励。 [46] 设计/方法/方法与考虑简单车辆模型（四分之一车辆模型或半车模型）和/或简化道路轮廓（例如谐波激励）和/或执行单目标优化和/或执行动态分析的论文不同在时域，本文提出了一种有效且快速的方法，用于对在不规则路面上行驶的整车模型（包括驾驶员座椅）的悬架系统进行多目标优化，其动态响应在频域中确定，大大减少了计算时间。 [47] Matlab 2019a 软件用于模拟以颠簸路面作为激励干扰的悬架模型。 [48] 从这些道路剖面收集的激励信号也用于子系统振动台和虚拟模拟，这些模拟正在逐渐取代物理整车测试和验证。 [49] 在获得最优设计方案后，使用 IPG/CarMaker 通过在 23 公里长的乡村道路上分配道路剖面来模拟最优方案。 [50]
Random Road Profile
The responses of a vehicle have been analysed under the Indian average random road profile (ISO8608) against the conventional passive suspension system. [1] Since we obtained the suitable damping characteristics that met the requirements under random road profiles and bumpy roads, the realization of these characteristics will enable us to satisfy the driving requirements. [2] By evaluating the performance at a random road profile, it is shown that both ride comfort and road holding (steering stability) can be enhanced by utilizing the fast-response MR damper. [3] The road model used in the study has been modeled according to non-random road profile mathematical formulation considering periodical and discrete road profile cases. [4] Vehicle dynamics model in type of 1/4 is used for vibration analysis under the effect of random road profile with different grades. [5] Stress state of the details of suspension of a cargo vehicle during the movement on random road profile was simulated. [6] For illustrative purposes, the coupled vibration problem of a regular truck traveling on a random road profile over a typical Brazilian bridge is analyzed. [7] The dynamic model consists of a lumped parameter mass-spring-dashpot model of seven degrees of freedom (7DOF) and used for the prediction of the head acceleration in the time domain and peak transmissibility ratio in the frequency domain under a sinusoidal wave excitation and random road profile excitations of different road classes and vehicle speeds. [8] Conclusion Thus, for a random road profile, it is better to choose the half car as a simplified vehicle model. [9]在印度平均随机道路剖面 (ISO8608) 下对传统被动悬架系统的车辆响应进行了分析。 [1] 由于我们获得了在随机道路剖面和颠簸路面下满足要求的合适阻尼特性，这些特性的实现将使我们能够满足驾驶要求。 [2] 通过评估随机路况下的性能，表明通过使用快速响应的 MR 阻尼器可以提高乘坐舒适性和抓地力（转向稳定性）。 [3] 研究中使用的道路模型是根据考虑周期性和离散道路剖面情况的非随机道路剖面数学公式建模的。 [4] 采用1/4型车辆动力学模型，进行不同等级随机道路剖面作用下的振动分析。 [5] 模拟了货车在随机道路剖面运动过程中悬挂细节的应力状态。 [6] 出于说明目的，分析了一辆普通卡车在随机道路剖面上行驶在典型的巴西桥梁上的耦合振动问题。 [7] 动力学模型由一个七自由度（7DOF）的集总参数质量-弹簧-缓冲器模型组成，用于预测正弦波激励和随机条件下的时域头部加速度和频域峰值传递率比。不同道路等级和车速的道路轮廓激励。 [8] nan [9]
Different Road Profile
Afterwards, an optimal solution is sought between the Pareto alternatives provided by the two road cases, in order for the tyre wear levels to be less affected under different road profiles. [1] Different road profiles are used to test the active suspension system response, such as a step input of 0. [2] The simulation results illustrate the effectiveness of the proposed integrated control strategy under different road profiles and maneuvers. [3]之后，在两种路况提供的帕累托备选方案之间寻求最优解，以减少不同路况下轮胎磨损程度的影响。 [1] 使用不同的道路剖面来测试主动悬架系统的响应，例如步输入为 0。 [2] nan [3]
Unknown Road Profile
The objective of the LPV observer is to minimize the effects of bounded unknown input disturbances (unknown road profile and measurement noises) on the state estimation errors through an H∞ criterion, while the damper nonlinearity is bounded using a Lipschitz condition. [1] The estimation method of the damper force is developed using a NLPV observer whose objectives are to minimize the effects of bounded unknown road profile disturbances and measurement noises on the estimation errors in the H∞ framework. [2]Sinusoidal Road Profile
The sinusoidal road profile is set as the disturbance of this system. [1] In this paper, a six-DOF three-wheeler is modeled and the dynamic response of the three-wheeler is measured when the vehicle is moving on bump, random, sinusoidal road profiles, by using ADAMS–MATLAB Simulink co-simulation. [2]正弦道路轮廓被设置为该系统的扰动。 [1] nan [2]
Stochastic Road Profile
A covariance analysis related to standard deviations of cost function criteria with respect to stochastic road profile input is carried out for half-car models with two and four degrees of freedom. [1] by comparing standard deviations of the criteria-reflected system outputs with respect to stochastic road profile input. [2]Variou Road Profile
This work aims to perform kinematic and compliance analysis on comprehensive quarter car model of McPherson suspension system to validate its reliability with respect to various road profiles and development of control algorithm to control its stiffness. [1] Introduction Vibration suspension system is used in the automobiles to mitigate the excitations that can come from the travel over various road profiles. [2]本工作旨在对 McPherson 悬架系统的综合四分之一汽车模型进行运动学和合规性分析，以验证其在各种路况下的可靠性，并开发控制算法来控制其刚度。 [1] 简介 振动悬架系统用于汽车中，以减轻可能来自各种道路剖面行驶的激励。 [2]
Bump Road Profile
The Matlab 2019a software is used to simulate the suspension models with bump road profiles as excitation disturbance. [1] In addition to this, the performance of all the three controllers are also evaluated for uncertainty in sprung mass and bump height and also for multiple bumps road profiles. [2]Matlab 2019a 软件用于模拟以颠簸路面作为激励干扰的悬架模型。 [1] 除此之外，还评估了所有三个控制器的性能，以评估簧载质量和颠簸高度的不确定性以及多个颠簸路况。 [2]
road profile disturbance
The predominant role of a piezoelectric harvester system in Vibration Energy Harvesting (VEH) is to gather vibrations energy caused by road profile disturbances. [1] The estimation method of the damper force is developed using a NLPV observer whose objectives are to minimize the effects of bounded unknown road profile disturbances and measurement noises on the estimation errors in the H∞ framework. [2]压电收集器系统在振动能量收集 (VEH) 中的主要作用是收集由道路轮廓扰动引起的振动能量。 [1] nan [2]
road profile input
A covariance analysis related to standard deviations of cost function criteria with respect to stochastic road profile input is carried out for half-car models with two and four degrees of freedom. [1] by comparing standard deviations of the criteria-reflected system outputs with respect to stochastic road profile input. [2]road profile excitation
Exemplary standard road profile excitations are also conducted to demonstrate the applicability of the designed system for frequency-domain testing of components in the vehicle suspension systems. [1] The dynamic model consists of a lumped parameter mass-spring-dashpot model of seven degrees of freedom (7DOF) and used for the prediction of the head acceleration in the time domain and peak transmissibility ratio in the frequency domain under a sinusoidal wave excitation and random road profile excitations of different road classes and vehicle speeds. [2]还进行了示例性标准道路轮廓激励，以证明所设计系统在车辆悬架系统中的组件的频域测试中的适用性。 [1] 动力学模型由一个七自由度（7DOF）的集总参数质量-弹簧-缓冲器模型组成，用于预测正弦波激励和随机条件下的时域头部加速度和频域峰值传递率比。不同道路等级和车速的道路轮廓激励。 [2]