Electric Vehicles Mileage Extender Kinetic Energy Storage

Abstract

The proposed paper considers small urban vehicles with electric hybrid propulsion systems. Energy demands are examined on the basis of European drive cycle (NEUDC) and on an energy recuperation coefficient and are formulated for description of cycle energy transfers. Numerical simulation results show real possibilities for increasing in achievable vehicle mileage at the same energy levels of a main energy source -the electric battery. Kinetic energy storage (KES), as proposed to be used as an energy buffer and different structural schemes of the hybrid propulsion system are commented. Minimum energy levels for primary (the electric battery) and secondary (KES) sources are evaluated. A strategy for reduced power flows control is examined, and its impact on achievable vehicle mileage is investigated. Results show an additional increase in simulated mileage at the same initial energy levels.

A Markov Model for Subway Composite Energy Prediction

“…When the train runs at certain intervals, it is crucial to construct a predictive model for each stage of the travel process using information such as the current vehicle speed and acceleration to predict the speed and acceleration within a finite period. This prediction can be applied to forecast the operational state of the train in the time domain and calculate the power demand of the train for use in the later energy optimization control problem [37][38][39]. The control effect is strongly related to the control accuracy of operating speed prediction, while the train running state is also influenced by the external environment and the driver's state, which are unknown.…”