Multi-Objective Optimization for Plug-In 4WD Hybrid Electric Vehicle Powertrain

Abstract

This paper focuses on the parameter optimization for the CVT (a continuously variable transmission) based plug-in 4WD (4-wheel drive) hybrid electric vehicle powertrain. First, the plug-in 4WD hybrid electric vehicle (plug-in 4WD HEV)’s energy management strategy based on the CD (charge depleting) and CS (charge sustain) mode is developed. Then, the multi-objective optimization’s mathematical model, which aims at minimizing the electric energy consumption under the CD stage, the fuel consumption under the CS stage and the acceleration time from 0–120 km/h, is established. Finally, the multi-objective parameter optimization problem is solved using an evolutionary based non-dominated sorting genetic algorithms-II (NSGA-II) approach. Some of the results are compared with the original scheme and the classical weight approach. Compared with the original scheme, the best compromise solution (i.e., electric energy consumption, fuel consumption and acceleration time) obtained using the NSGA-II approach are reduced by 1.21%, 6.18% and 5.49%, respectively. Compared with the weight approach, the Pareto optimal solutions obtained using NSGA-II approach are better distributed over the entire Pareto optimal front, as well as the best compromise solution is also better.

Optimization of Powertrain in EV

“…The Coulomb friction M is included in both models. In the block diagrams, three energy storages are considered that are given by Formula (12). The diameter of the wheels is d w , which changes rotational motion to longitudinal, and is found in every scheme because the torque M also depends on d w (6).…”

“…The parameter optimization for the CVT (continuously variable transmission) in 4wheel drive HEV is considered in [12], where evolutionary based non-dominated sorting genetic algorithms-II (NSGA-II) is used.…”

A Hybrid Multi-Objective Optimization Method Based on NSGA-II Algorithm and Entropy Weighted TOPSIS for Lightweight Design of Dump Truck Carriage

“…Liu et al [11] presented an improved particle swarm optimization algorithm to conduct the lightweight design of auto-body by considering its crashworthiness. Wang et al [12] conducted the multi-objective parameter optimization of the powertrain and control strategy of a hybrid electric vehicle, which achieved energy and fuel-saving as well as power performance improvement. Xie et al [13] performed the multi-objective lightweight design of S-rails of cab-in-white of the commercial vehicle to reduce its weight and improve the crashworthiness performances.…”

Performance Analysis of a Hybrid Electric Vehicle with Multiple Converter Configuration

“…Currently, more efficient transportation technologies such as electric vehicles (EVs), hybrid vehicles (HVs), and hybrid electric vehicles (HEVs) are being explored. The first uses batteries (Bs) [2,3], the second uses a combination of internal combustion and electrical power [3,4], and the latter has an energy storage system that can 2 of 17 be composed of ultracapacitors (UCs), batteries (Bs), and fuel cells [5][6][7]. EVs and HEVs today are considered a viable alternative since they offer an intelligent and efficient transport system without polluting emissions [8][9][10][11][12].…”