A charging management-based intelligent control strategy for extended-range electric vehicles

Abstract

Abstract:To fully take advantage of external charging conditions and reduce fuel consumption for extended-range electric vehicles, a charging management-based intelligent control strategy is proposed. The intelligent control strategy is applied to different driving patterns based on the various characteristics of urban roads. When the vehicle is driving on arterial roads, a constant power control strategy is applied. When the driver decides to go to a charging station, the extender-off time can be determined based on the current state of the vehicle and the distance to the charging station. When the vehicle is driving on an expressway, a power follower control strategy is applied. The range-extender engine is controlled to work over a wide variety of regions to obtain optimum fuel economy. The simulation results indicate that as the vehicle arrives at the charging station, the proposed charging management-based intelligent control strategy has made the state of charge reach the lowest permissible level after the driver made the decision to charge at the charging station. Therefore, the driver can charge the vehicle with as much clean electric energy as possible from the charging station.

A Systematic Review of Technologies, Control Methods, and Optimization for Extended-Range Electric Vehicles

“…The range extender comprises a fuel tank, an internal combustion engine, and a permanent magnet synchronous generator [3,, as shown in Figure 2. The structure is mechanically decoupled between the RE and the wheels of the EV.…”

“…Compared to internal combustion engine vehicles (ICEVs), EREVs reduce emissions and are considered a favorable alternative [1,2]. EREVs, compared with EV, not only have the advantage of "zero fuel consumption and zero emissions"; they also effectively solve the problem of having an inadequate driving range due to power storage limitations in batteries [3]. This paper presents a systematic review on the subject of EREVs.…”

Intelligent Energy Management Control for Extended Range Electric Vehicles Based on Dynamic Programming and Neural Network

“…If the EREV finishes the trip and reaches the charging station with low battery energy, it can store more clean energy from the grid. Then, the fuel consumption of the extender can be reduced on the next trip for the same total energy demand [9,10].…”