scholarly journals Multidisciplinary Design of Electric Vehicles Based on Hierarchical Multi-Objective Optimization

2019 ◽  
Vol 141 (9) ◽  
Author(s):  
Kesavan Ramakrishnan ◽  
Gianpiero Mastinu ◽  
Massimiliano Gobbi
Keyword(s):  
Complex Systems ◽  
Electric Vehicles ◽  
Optimal Solution ◽  
System Level ◽  
Optimization Approach ◽  
Analytical Target Cascading ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Subsystem Level ◽  
Target Cascading

A method for the optimal design of complex systems is developed by effectively combining multi-objective optimization and analytical target cascading techniques. The complex systems with high dimensionality are partitioned into manageable subsystems that can be optimized using dedicated algorithms. The multiple objective functions in each subsystem are treated simultaneously, and the interactions between subsystems are managed using linking variables and shared variables. The analytical target cascading algorithm ensures the convergence of the optimal solution that meets the system level targets while complying with the subsystem level constraints. A design optimization of electric vehicles with in-wheel motors is formulated as a two-level hierarchical scheme where the top level has a model representing the electric vehicle and the bottom level contains models of battery and suspension. The vehicle model includes an electric motor model and a power electronics model. Pareto-optimal solutions are derived holistically. The effectiveness of the proposed method for optimizing the complex systems is compared against the conventional all-in-one optimization approach.

Multi-Objective Optimization for a Novel Electrostatic-Feedback Micro-Sensor Based on Genetic Algorithm

2007 ◽  
Author(s):  
Yongquan Wang ◽  
Hualing Chen ◽  
Zhiying Ou ◽  
Xueming He
Keyword(s):  
Genetic Algorithm ◽  
Multidisciplinary Design Optimization ◽  
Optimal Solution ◽  
Optimization Approach ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Micro Sensor ◽  
Energy Relations

In this paper, we present the multi-objective optimization for an entire microsystem, a novel capacitive electrostatic feedback accelerometer. From the energy relations of the coupled electrostatic-field, the dynamic model of the system is constructed. Aiming at the global performance, a multi-objective optimization model, where sensitivity, resolution and damping resonant frequency are selected as objectives, is established based on the concept of multidisciplinary design optimization (MDO). Genetic algorithm (GA) is used to solve this problem, and compared with a traditional optimization approach, sequence quadratic programming (SQP). Both the two algorithms can achieve our aim commendably, and the optimal solution given by GA is more satisfied. The research provides us a good foundation to develop the stochastic and implicit parallel properties of GA to obtain Pareto optimal solutions.

scholarly journals Bounded Target Cascading in Hierarchical Design Optimization

2014 ◽  
Vol 6 ◽  
pp. 790620
Author(s):  
Xiaoling Zhang ◽  
Debiao Meng ◽  
Ruan-Jian Yang ◽  
Zhonglai Wang ◽  
Hong-Zhong Huang
Keyword(s):  
Design Optimization ◽  
Large Scale ◽  
System Level ◽  
Weighted Sum ◽  
Analytical Target Cascading ◽  
Hierarchical Design ◽  
Subsystem Level ◽  
Target Cascading ◽  
The Common ◽  
Single Objective

For large scale systems, as a hierarchical multilevel decomposed design optimization method, analytical target cascading coordinates the inconsistency between the assigned targets and response in each level by a weighted-sum formulation. To avoid the problems associated with the weighting coefficients, single objective functions in the hierarchical design optimization are formulated by a bounded target cascading method in this paper. In the BTC method, a single objective optimization problem is formulated in the system level, and two kinds of coordination constraints are added: one is bound constraint for the design points based on the response from each subsystem level and the other is linear equality constraint for the common variables based on their sensitivities with respect to each subsystem. In each subsystem level, the deviation with target for design point is minimized in the objective function, and the common variables are constrained by target bounds. Therefore, in the BTC method, the targets are coordinated based on the optimization iteration information in the hierarchical design problem and the performance of the subsystems, and BTC method will converge to the global optimum efficiently. Finally, comparisons of the results from BTC method and the weighted-sum analytical target cascading method are presented and discussed.

scholarly journals Exergy-Based Multi-Objective Optimization of an Organic Rankine Cycle with a Zeotropic Mixture

Entropy ◽  
2021 ◽  
Vol 23 (8) ◽  
pp. 954
Author(s):  
Zineb Fergani ◽  
Tatiana Morosuk ◽  
Djamel Touil
Keyword(s):  
Organic Rankine Cycle ◽  
Optimal Solution ◽  
Rankine Cycle ◽  
Working Fluid ◽  
Particle Swarm Algorithm ◽  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Benzene Toluene ◽  
Zeotropic Mixture

In this paper, the performance of an organic Rankine cycle with a zeotropic mixture as a working fluid was evaluated using exergy-based methods: exergy, exergoeconomic, and exergoenvironmental analyses. The effect of system operation parameters and mixtures on the organic Rankine cycle’s performance was evaluated as well. The considered performances were the following: exergy efficiency, specific cost, and specific environmental effect of the net power generation. A multi-objective optimization approach was applied for parametric optimization. The approach was based on the particle swarm algorithm to find a set of Pareto optimal solutions. One final optimal solution was selected using a decision-making method. The optimization results indicated that the zeotropic mixture of cyclohexane/toluene had a higher thermodynamic and economic performance, while the benzene/toluene zeotropic mixture had the highest environmental performance. Finally, a comparative analysis of zeotropic mixtures and pure fluids was conducted. The organic Rankine cycle with the mixtures as working fluids showed significant improvement in energetic, economic, and environmental performances.

Sign in / Sign up

Export Citation Format

Share Document