Research progress and application of computational method for hydrodynamic noise from air-water interface北大核心CSCD

含水气界面水动力噪声是船海工程结构物经常遇到的一类典型重要噪声,具有机理复杂、声源形式多样、传播影响因素众多等特点。含水气界面水动力噪声与自由面相互作用,受空化、水气泡混合流等影响,对舰船的隐蔽性造成很多负面影响,具有重要的研究意义。分别从自由面噪声、空化噪声和水气泡混合流噪声3个方面进行介绍,并阐述相应噪声的计算方法以及在噪声计算时需要考虑的关键问题和目前所采用的解决方案。最后,展望未来的研究发展方向。     

Adaptive neuron control using an integrated error approach with application to active suspensions

This paper proposes a new neuron control strategy for an active vehicle suspension system, with the emphasis on the study of multivariable and uncertain suspension characteristics. The novelty of this strategy is in the use of integrated error, which consists of multiple output errors in the regulated plant. By combining the integrated error approach with the traditional neuron control (TNC), integrated error neuron control (IENC) is presented. It provides a direct control to the multiple outputs of the control plant simultaneously. Taking a quarter-car model as an example, the proposed control strategy is applied and comparative simulations are carried out with various vehicle parameters and road input conditions. Simulation results prove the effectiveness and robustness of the proposed IENC method. In addition, the newly proposed neuron scheme provides a simple yet efficient new possibility for the control of a class of uncertain multivariable systems similar to an active vehicle suspension.     

Realization of pmp-based control for hybrid electric vehicles in a backward-looking simulation

Optimal control is generally not possible without information about the future coming up, and it is not easy to obtain an optimal solution even though the information is given a priori. In this paper, a control concept based on Pontryagin’s Minimum Principle (PMP) is introduced as an efficient solution to generate an optimal control trajectory for Hybrid Electric Vehicles (HVEs) when the performance of the vehicles is evaluated on scheduled driving cycles at a simulation level. The main idea of the control concept is to minimize Hamiltonian, which is interpreted as equivalent fuel consumption, and the Hamiltonian is characterized by a co-state, which is interpreted as a weighting factor for the electrical usage. A key aspect of the control problem is that an appropriate initial condition of the co-state is required to satisfy the boundary condition of the problem. In this study, techniques to calculate the Hamiltonian in different hybrid configurations are introduced, and a methodology to look for the initial condition of the co-state is studied, so that the controller is able to realize a desired State Of Charge (SOC) trajectory. To address the issue, we utilize a shooting method with multiple initial conditions based on the concept of the Newton-Raphson method, and all these techniques are realized in a backward looking simulator. The simulation results show that the PMP-based control is a very efficient approach to produce the optimal control trajectory, and the performance is compared to the optimal solution solved by Dynamic Programming (DP).     

Application of a modified thermostatic control strategy to parallel mild HEV for improving fuel economy in urban driving conditions

A modified thermostatic control strategy is applied to the powertrain control of a parallel mild hybrid electric vehicle (HEV) to improve fuel economy. This strategy can improve the fuel economy of a parallel mild HEV by operating internal combustion engine (ICE) in a high-efficiency region. Thus, in this study, experiments of a parallel mild HEV were conducted to analyze the characteristics of the hybrid electric powertrain and a numerical model is developed for the vehicle. Based on the results, the thermostatic control strategy was modified and applied to the vehicle model. Also, battery protection logic by using electrochemical battery model is applied because the active usage of battery by thermostatic control strategy can damage the battery. The simulation results of the vehicle under urban driving conditions show that the thermostatic control strategy can improve the vehicle’s fuel economy by 3.7 % compared with that of the conventional strategy. The results also suggest that the trade-off between the fuel economy improvement by efficient ICE operation and the battery life reduction by active battery usage should be carefully investigated when a thermostatic control strategy is applied to a parallel mild HEV.     

���зֲ�����Ϣ��ģ��

熵最大化方法被广泛应用于交通规划，为交通需求预测模型提供了理论依据.本文使用信息论中的熵概念描述居民出行分布，并根据最大信息熵理论提出了基于原点矩典型特征量约束条件下的出行分布模型，详细阐述了模型中各个参数的实际含义，该模型是一个普适性模型，其具体形式决定于最高阶原点矩阶数的取值，此值对模型精度及参数标定难易程度有重要影响.为确定模型参数，提出了实用的参数标定方法.由于模型中原点矩的最高阶数对模型精度有较大影响，为找到两者之间的关系，利用长春市出行调查数据研究了四种出行方式分别时应于五种原点矩最高阶数的模型拟合情况.因文中所建立的模型是一系列模型，为比较其描述问题的优劣差异，按照最大信息熵原理给出了确定系统分布的熵方法，并运用该方法对前述模型进行了比较.调查数据的验证结果表明，出行分布的信息熵模型可以正确地描述出行分布规律，熵方法可以简单有效地评价不同模型对同一问题描述的优劣差异.本文提出的熵模型和熵方法对城市交通规划具有指导意义.     

Evasive manoeuvres with a steering robot

In the pursuit of an objective rating on vehicle stability performance, it is always desirable to reduce disturbances and inconsistencies during experimental evaluations, especially the ones introduced by human drivers. This paper presents the development of a steering robot designed for closed-loop steering tasks during evasive manoeuvres. It describes the controller structure and discusses experimental results, in addition to simulation/vehicle model verifications and theoretical control analysis.     

Design and implementation of a UPnP-can gateway for automotive environments

In this paper, we propose a universal plug and play (UPnP) — controller area network (CAN) gateway system using UPnP middleware for interoperability between external smart devices and an in-vehicle network. The proposed gateway consists of a UPnP communication device, a CAN communication device, and a device translator layer. In-vehicle devices are not usually IP-based, so we implemented an in-vehicle device manager in the UPnP communication device which is in the gateway. We developed a vehicle simulator to produce real vehicular data for performance analysis. The CAN communication device transmits and receives real-time vehicle data between the real vehicular simulator and external devices through the UPnP. The device translator layer configures a message frame for enabling seamless data input and output between the CAN and UPnP protocols. After implementation, we generated an internal-external service request and tested the result. Finally, we confirmed the service request and operation between external devices and the internal vehicular device. Additionally, for a variety of external device numbers and communication environments, we demonstrated the gateway performance by measuring the round trip time (RTT) for overall service implementation.