Research on Novel Fuzzy Control Strategy of Hybrid Electric Vehicles Based on Feature Selection Genetic Algorithm

Abstract

We propose a novel fuzzy control strategy for hybrid electric vehicles (HEVs) based on the feature selection genetic algorithm of multivariate data, which greatly shortens the selection time of the optimal parameters of the traditional genetic algorithm. Firstly, we take the fuel consumption and emission of an HEV as the optimization index, and develop a novel fuzzy control method considering parameters of the fuzzy controller with high correlation with the objective function, in which the membership function parameter is optimized by the feature selection genetic algorithm. Finally, the performances of the fuzzy control strategy for an HEV and the novel fuzzy control strategy optimized by the feature selection genetic algorithm under the New European Driving Cycle (NEDC) and Urban Dynamometer Driving Schedule (UDDS) cycle conditions are analyzed and compared. The results show that the proposed fuzzy control can greatly improve the fuel economy and reduce the emission of HEVs.

Comprehensive Health Evaluation Model of Art Psychotherapy Using Genetic Algorithm

“…The specific meanings of the general assumptions are described as follows: Hypothesis a: compared with before and after intervention group A, spat group counseling (intervention group A) has significant differences in six aspects: self-harmony, depression, Eysenck personality type, social avoidance and anxiety, life orientation, optimism, and trait coping style [ 16 ]. Hypothesis AB: compared with control group B, spat group counseling has significant differences in six aspects: self-harmony, depression, Eysenck personality type, social avoidance and anxiety, life orientation, optimism, and trait coping style [ 17 ].…”

“…Hypothesis a: compared with before and after intervention group A, spat group counseling (intervention group A) has significant differences in six aspects: self-harmony, depression, Eysenck personality type, social avoidance and anxiety, life orientation, optimism, and trait coping style [ 16 ].…”

“…Standardized mutual information (NMI) is also called normalized mutual information; that is, standardize the value of mutual information to between [0, 1] through the standardization method, as shown in formula (16):…”

Research on Adaptive Two-Point Energy Management Strategy and Optimization for Range-Extended Electric Vehicle

“…Optimization-based EMS can be further divided into global optimization control and real-time optimization control. Among them, particle swarm optimization (PSO) [10], model predictive control (MPC) [11]- [13], genetic algorithm (GA) [14]- [16], dynamic programming (DP) [17]- [19], pseudospectral optimal control (PSOC) [20] and minimum principle (MP) [21]- [23] are widely used in solving EMS MOO problems. Considering battery life, Wang et al [24] proposed a novel EMS based on the improved deep Q-network (DQN) to reduce the driving cost of HEV, while considering the life and energy efficiency of lithium-ion batteries.…”