Multi-objective trade-off optimal control of energy management for hybrid system

Abstract

Currently, energy management control mainly focuses on single-objective optimization (SOO). Even if multi-objective optimization (MOO) problem is studied, it is often converted into an SOO problem by using the weighted sum method. Obviously, it cannot really reflect the essential strengths of MOO. In this paper, a parallel hybrid electric vehicle is taken as the research object. The fuel economy, emissions, and drivability performance are taken as optimization objectives. The parameters of energy management and driveline system are optimized. Considering the constraint conditions of the dynamic performance and charge balance, the fast non-dominated sorting differential evolution algorithm (NSDEA) is proposed to solve the multi-objective optimization problem. Then multi-group sets of Pareto solutions with good distribution and convergence are obtained. The simulation results of NSDEA show that the fuel economy is increased by 20.26% on average. The emissions evaluation index is optimized by 11.33% on average, and the maximum carbon monoxide (CO) optimization value reaches 21.9%. The average of drivability evaluation index (jerk) is up to 20.84%, and 40.32% for maximum. Obviously, the above obtained results are discrete points. They only represent some optimal solutions. Based on the above sets, the locally weighted scatter plot smoothing method is used to fit continuous curve and surfaces. Then, the multi-objective Pareto trade-off optimal control surface is established to further obtain the optimal solutions. This study can provide more reference for the optimal control strategy and lay a foundation for multi-objective energy management of the actual vehicle.

Selection of best process parameters for friction stir welded dissimilar Al-Cu alloy: a novel MCDM amalgamated MORSM approach

“…Trade-off analysis maintains a balance within the system parameters such that the entire system is at a maximum profit [49]. Multi-objective response surface methodology (MORSM) is one such type of method that is widely applied in the engineering world for drawing a nonchalant result for a problem having various responses or input variables [42,[50][51][52].…”

“…In statistics, the multicollinearity tests the dependency level for the independent factors. Variance inflation factor (VIF) determines the multicollinearity among the independent variables [42]. Regression equation determines the relationship between the dependent and independent variables.…”

Real-time nonlinear model predictive energy management system for a fuel-cell hybrid vehicle

“…In Eqs. (20) and (21), u k , ̃k and k are the constraints on state variables which have been defined on dynamic parameters. ̃N is the function which has to be minimized based on mentioned constraints.…”

“…The main types of resistive forces which have been mentioned in Eq. (25) are aerodynamic resistive force, force due to inclination of the track (gravity) and inertial forces [3,20]. (23) ⎧ ⎪ ⎨ ⎪ ⎩ P fc,min ≤ P fc ≤ P fc,max P brk,min ≤ P brk ≤ P brk,max 0.2 ≤ SOC ≤ 0.9 0 ≤ P H 2 ≤ 2.5 (atm) .…”

Synthesis of multi-mode electric-mechanical variable transmission based on 4-DOF planetary gear mechanisms

“…It has a certain guiding effect on the sequence of modes. Deng et al 28 adopted a fast non-dominated sorting differential evolution algorithm to optimize the existing hybrid electric vehicles and sequence their modes. Pei et al 14 proposed a rapid dynamic programing algorithm to screen out the economic schemes from many alternative hybrid electrical vehicles based on Toyota Prius.…”