Energy Efficiency and Emission Testing for Connected and Automated Vehicles Using Real-World Driving Data

By using the onboard sensing and external connectivity technology, connected and automated vehicles (CAV) could lead to improved energy efficiency, better routing, and lower traffic congestion. With the rapid development of the technology and adaptation of CAV, it is more critical to develop the universal evaluation method and the testing standard which could evaluate the impacts on energy consumption and environmental pollution of CAV fairly, especially under the various traffic conditions. In this paper, we proposed a new method and framework to evaluate the energy efficiency and emission of the vehicle based on the unsupervised learning methods. Both the real-world driving data of the evaluated vehicle and the large naturalistic driving dataset are used to perform the driving primitive analysis and coupling. Then the linear weighted estimation method could be used to calculate the testing result of the evaluated vehicle. The results show that this method can successfully identify the typical driving primitives. The couples of the driving primitives from the evaluated vehicle and the typical driving primitives from the large real-world driving dataset coincide with each other very well. This new method could enhance the standard development of the energy efficiency and emission testing of CAV and other off-cycle credits

Effects of periodically modulated coupling on amplitude death in nonidentical oscillators

The effects of periodically modulated coupling on amplitude death in two coupled nonidentical oscillators are explored. The AD domain could be significantly influenced by tuning the modulation amplitude and the modulation frequency of the modulated coupling strength. There is an optimal value of modulation amplitude for the modulated coupling with which the largest AD domain is observed in the parameter space. The AD domain is enlarged with the decrease of the modulation frequency for a given small modulation amplitude, while is shrunk with decrease of the modulation frequency for a given large modulation amplitude. The mechanism of AD in the presence of periodic modulation in the coupling is investigated via the local condition Lyapunov exponent of the coupled system. The stability of AD state can be well characterized by conditional Lyapunov exponent. The coupled system experiencing from the oscillatory state to AD is clearly indicated by the observation that the conditional Lyapunov exponent transits from positive to negative. Our results are helpful to many potential applications for the research of neuroscience and dynamical control in engineering.Comment: 11 figures, 8 page

Current Dissipation in Thin Superconducting Wires: Accurate Numerical Evaluation Using the String Method

Current dissipation in thin superconducting wires is numerically evaluated by using the string method, within the framework of time-dependent Ginzburg-Landau equation with a Langevin noise term. The most probable transition pathway between two neighboring current-carrying metastable states, continuously linking the Langer-Ambegaokar saddle-point state to a state in which the order parameter vanishes somewhere, is found numerically. We also give a numerically accurate algorithm to evaluate the prefactors for the rate of current-reducing transitions.Comment: 25 pages, 5 figure