It allows recognition between three driving modes: urban, suburban and highway. A real-time control strategy is then defined based on fuzzy logic using DCRA.

It allows recognition between three driving modes: urban, suburban and highway. A real-time control strategy is then defined based on fuzzy logic using DCRA.

Abstract—The most adapted energy management in hybrid electric vehicles depends on the current driving situation. This paper describes a novel control ...

Apr 15, 2023 · This study can be used as a guidance to select driving condition recognition method for adaptive vehicle energy management.

Jul 11, 2022 · This paper proposed an adaptive energy management strategy (A-EMS) based on intelligent recognition of driving cycle (IRDC) by the back propagation neural ...

In this paper, the modeling and regulation of a hybrid electric vehicle is explored to optimize system performance for fuel-efficiency.

In order to improve the fuel economy of PHEV, an adaptive energy management strategy is designed on the basis of the intelligent prediction of driving cycles.

Global optimization provides the ultimate level of cycle adaptation in this category by using full second-by-second a priori knowledge of the drive cycle.

The primary improvement of the proposed A-ECMS over other algorithms with similar objectives is that it does not require the knowledge of future driving cycles ...

Apr 16, 2012 · This paper studies the supervised driving cycle recognition using pattern recognition approach. With pattern recognition method, a driving cycle is represented ...