Direct Yaw Moment Control for Distributed Drive Electric Vehicle Handling Performance Improvement

For a distributed drive electric vehicle（DDEV） driven by four in-wheel motors, advanced vehicle dynamic control methods can be realized easily because motors can be controlled independently, quickly and precisely. And direct yaw-moment control（DYC） has been widely studied and applied to vehicle stability control. Good vehicle handling performance： quick yaw rate transient response, small overshoot, high steady yaw rate gain, etc, is required by drivers under normal conditions, which is less concerned, however. Based on the hierarchical control methodology, a novel control system using direct yaw moment control for improving handling performance of a distributed drive electric vehicle especially under normal driving conditions has been proposed. The upper-loop control system consists of two parts： a state feedback controller, which aims to realize the ideal transient response of yaw rate, with a vehicle sideslip angle observer; and a steering wheel angle feedforward controller designed to achieve a desired yaw rate steady gain. Under the restriction of the effect of poles and zeros in the closed-loop transfer function on the system response and the capacity of in-wheel motors, the integrated time and absolute error（ITAE） function is utilized as the cost function in the optimal control to calculate the ideal eigen frequency and damper coefficient of the system and obtain optimal feedback matrix and feedforward matrix. Simulations and experiments with a DDEV under multiple maneuvers are carried out and show the effectiveness of the proposed method： yaw rate rising time is reduced, steady yaw rate gain is increased, vehicle steering characteristic is close to neutral steer and drivers burdens are also reduced. The control system improves vehicle handling performance under normal conditions in both transient and steady response. State feedback control instead of model following control is introduced in the control system so that the sense of control intervention to drivers is relieved.

Fatigue Performance of Orthotropic Steel Decks in Super-Wide Steel Box Girder Considering Transverse Distribution of Vehicle Load

This study presents an investigation on the fatigue analysis of four types of details on orthotropic steel decks(OSDs)for a cable-stayed super-wide steel box girder bridge based on finite-element analysis(FEA)with vehicle transverse distribution model(VTDM).A high-fidelity 3D FE model verified by the static load test is established to satisfy the fatigue analysis accuracy.The stress behavior of super-wide steel box girders under the vehicle load at different lane locations is investigated.Then,considering the effect of VTDM,the fatigue life analysis of four typical details is performed using the Miner cumulative damage rule.The results show that the vehicle transverse location has a great influence on the stress behavior of details with sharp influence surface,and the stress ranges in the outermost lane are larger than those in other lanes,indicating that the details of OSD in the outermost lane are prone to fatigue.The fatigue life analysis indicates that the diaphragm cutout is more prone to fatigue than other details,which should be carefully treated in bridge maintenance.

Bibliometric analysis and system review of vehicle routing optimization for emergency material distribution

Determining the optimal vehicle routing of emergency material distribution(VREMD)is one of the core issues of emergency management,which is strategically important to improve the effectiveness of emergency response and thus reduce the negative impact of large-scale emergency events.To summarize the latest research progress,we collected 511VREMD-related articles published from 2010 to the present from the Scopus database and conducted a bibliometric analysis using VOSviewer software.Subsequently,we cautiously selected 49 articles from these publications for system review;sorted out the latest research progress in model construction and solution algorithms;and summarized the evolution trend of keywords,research gaps,and future works.The results show that domestic scholars and research organizations held an unqualified advantage regarding the number of published papers.However,these organizations with the most publications performed poorly regarding the number of literature citations.China and the US have contributed the vast majority of the literature,and there are close collaborations between researchers from both countries.The optimization model of VREMD can be divided into single-,multi-,and joint-objective models.The shortest travel time is the most common optimization objective in the single-objective optimization model.Several scholars focus on multiobjective optimization models to consider conflicting objectives simultaneously.In recent literature,scholars have focused on the impact of uncertainty and special events(e.g.,COVID-19)on VREMD.Moreover,some scholars focus on joint optimization models to optimize vehicle routes and central locations(or material allocation)simultaneously.Solution algorithms can be divided into two primary categories,i.e.,mathematical planning methods and intelligent evolutionary algorithms.The branch and bound algorithm is the most dominant mathematical planning algorithm,while genetic algorithms and their enhancements are the most commonly used intelligent evolutionary algorithms.It is shown that the nondominated sorting genetic algorithmⅡ(NSGA-Ⅱ)can effectively solve the multiobjective model of VREMD.To further improve the algorithm’s performance,researchers have proposed improved hybrid intelligent algorithms that combine the advantages of NSGA-Ⅱand certain other algorithms.Scholars have also proposed a series of optimization algorithms for specific scenarios.With the development of new technologies and computation methods,it will be exciting to construct optimization models that consider uncertainty,heterogeneity,and temporality for large-scale real-world issues and develop generalized solution approaches rather than those applicable to specific scenarios.