Shared autonomous electric vehicle design and operations under uncertainties: a reliability-based design optimization approach

2019 ◽  
Vol 61 (4) ◽  
pp. 1529-1545
Author(s):  
Ungki Lee ◽  
Namwoo Kang ◽  
Ikjin Lee
Keyword(s):  
Design Optimization ◽  
Electric Vehicle ◽  
Vehicle Design ◽  
Optimization Approach ◽  
Reliability Based Design Optimization ◽  
Reliability Based Design

Reliability-based design optimization of electromagnetic shielding structure using neural networks and real-coded genetic algorithm

2014 ◽  
Vol 228 (18) ◽  
pp. 3471-3481 ◽  
Author(s):  
Heeralal Gargama ◽  
Sanjay K Chaturvedi ◽  
Awalendra K Thakur
Keyword(s):  
Genetic Algorithm ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Design Optimization ◽  
Electromagnetic Shielding ◽  
Optimization Approach ◽  
Reliability Based Design Optimization ◽  
Reliability Based Design ◽  
Design Variables ◽  
Real Coded Genetic Algorithm

The conventional approaches for electromagnetic shielding structures’ design, lack the incorporation of uncertainty in the design variables/parameters. In this paper, a reliability-based design optimization approach for designing electromagnetic shielding structure is proposed. The uncertainties/variability in the design variables/parameters are dealt with using the probabilistic sufficiency factor, which is a factor of safety relative to a target probability of failure. Estimation of probabilistic sufficiency factor requires performance function evaluation at every design point, which is extremely computationally intensive. The computational burden is reduced greatly by evaluating design responses only at the selected design points from the whole design space and employing artificial neural networks to approximate probabilistic sufficiency factor as a function of design variables. Subsequently, the trained artificial neural networks are used for the probabilistic sufficiency factor evaluation in the reliability-based design optimization, where optimization part is processed with the real-coded genetic algorithm. The proposed reliability-based design optimization approach is applied to design a three-layered shielding structure for a shielding effectiveness requirement of ∼40 dB, used in many industrial/commercial applications, and for ∼80 dB used in the military applications.

Improving the fatigue life of a vehicle knuckle with a reliability-based design optimization approach

2009 ◽  
Vol 139 (5) ◽  
pp. 1619-1632 ◽  
Author(s):  
R. d’Ippolito ◽  
M. Hack ◽  
S. Donders ◽  
L. Hermans ◽  
N. Tzannetakis ◽  
...  
Keyword(s):  
Fatigue Life ◽  
Design Optimization ◽  
Optimization Approach ◽  
Reliability Based Design Optimization ◽  
Reliability Based Design

Reliability-based design optimization for vertical vibrations of a modified electric vehicle using fourth-moment polynomial standard transformation method

2020 ◽  
Vol 234 (10-11) ◽  
pp. 2649-2664
Author(s):  
Sheng Wang ◽  
Lin Hua ◽  
Xinghui Han ◽  
Zhuoyu Su
Keyword(s):  
Design Optimization ◽  
Electric Vehicle ◽  
Optimization Problems ◽  
Computing Time ◽  
Optimization Procedure ◽  
Transformation Method ◽  
Vertical Vibration ◽  
Fourth Moment ◽  
Reliability Based Design Optimization ◽  
Reliability Based Design

This article presents a new reliability-based design optimization procedure for the vertical vibration issues raised by a modified electric vehicle using fourth-moment polynomial standard transformation method. First, the fourth-moment polynomial standard transformation method with polynomial chaos expansion is used to obtain the reliability index of uncertain constraints in the reliability-based design optimization which is highly precise and saves computing time compared with other common methods. Next, the half-car model with nonlinear suspension parameters for the modified electric vehicle is investigated, and the response surface methodology is adopted to approximate the complex and time-consuming vertical vibration calculation to the polynomial expressions, and the approximation is validated for reliability-based design optimization results within permissible error level. Then, reliability-based design optimization results under both deterministic and uncertain load parameters are shown and analyzed. Unlike the traditional vertical vibration optimization that only considers one or several sets of load parameters, which lacks versatility, this article presents the reliability-based design optimization with uncertain load parameters which is more suitable for engineering. The results show that the proposed reliability-based design optimization procedure is an effective and efficient way to solve vertical vibration optimization problems for the modified electric vehicle, and the optimization statistics, including the maximum probability interval, can provide references for other suspension dynamical optimization.

A Hybrid Reliability-Based Design Optimization Approach with Adaptive Chaos Control Using Kriging Model

2016 ◽  
Vol 13 (01) ◽  
pp. 1650006 ◽  
Author(s):  
Gang Li ◽  
Zeng Meng ◽  
Peng Hao ◽  
Hao Hu
Keyword(s):  
Design Optimization ◽  
Chaos Control ◽  
Pso Algorithm ◽  
Kriging Model ◽  
Target Point ◽  
Optimization Approach ◽  
Reliability Based Design Optimization ◽  
Local Optima ◽  
Reliability Based Design ◽  
Highly Nonlinear

Traditional reliability-based design optimization (RBDO) approaches are computationally expensive for complicated problems. To cope with this challenge, a surrogate-based hybrid RBDO approach for the problems with highly nonlinear constraints and multiple local optima is proposed in this study. Specifically, the adaptive chaos control (ACC) method is used to ensure the robustness of the most probable target point (MPTP) search process, and the particle swarm optimization (PSO) algorithm is utilized to conquer the barrier caused by multiple local optima. Three illustrative benchmark examples together with a 3 m diameter orthogrid stiffened shell for current launch vehicles are employed to demonstrate the efficiency and robustness of the proposed method.

Model Uncertainty Approximation Using a Copula-Based Approach for Reliability Based Design Optimization

2016 ◽  
Author(s):  
Hao Pan ◽  
Zhimin Xi ◽  
Ren-Jye Yang
Keyword(s):  
Design Optimization ◽  
Model Uncertainty ◽  
Design Space ◽  
Epistemic Uncertainty ◽  
Minimum Cost ◽  
Vehicle Design ◽  
Model Bias ◽  
Reliability Based Design Optimization ◽  
Reliability Based Design ◽  
Model Inadequacy

Reliability-based design optimization (RBDO) has been widely used to design engineering products with minimum cost function while meeting defined reliability constraints. Although uncertainties, such as aleatory uncertainty and epistemic uncertainty, have been well considered in RBDO, they are mainly considered for model input parameters. Model uncertainty, i.e., the uncertainty of model bias which indicates the inherent model inadequacy for representing the real physical system, is typically overlooked in RBDO. This paper addresses model uncertainty characterization in a defined product design space and further integrates the model uncertainty into RBDO. In particular, a copula-based bias correction approach is proposed and results are demonstrated by two vehicle design case studies.

Reliability-Based Design Optimization (RBDO) for Electric Vehicle Market Systems

2017 ◽  
Author(s):  
Ungki Lee ◽  
Namwoo Kang ◽  
Ikjin Lee
Keyword(s):  
Design Optimization ◽  
Electric Vehicle ◽  
Decision Makers ◽  
Battery Life ◽  
Engineering Systems ◽  
Reliability Based Design Optimization ◽  
Battery Lifetime ◽  
Reliability Based Design ◽  
Life Itself ◽  
Design For Market Systems

When designing a product, both engineering uncertainty and market heterogeneity should be considered to reduce the risk of failure in the market. Reliability-based design optimization (RBDO) approach allows decision makers to achieve target confidence in product performance under engineering uncertainty. Design for market systems (DMS) approach helps decision makers to find profit-maximized product design under market heterogeneity. This paper integrates RBDO and DMS approaches for an Electric vehicle (EV) design. Consumers’ preferences on warranted battery lifetime are heterogeneous while battery life itself is affected by various uncertainties such as battery characteristics and driving patterns. We optimized and compared four scenarios depending on whether engineering systems are deterministic or probabilistic, and whether a market is homogeneous or heterogeneous. The results provide some insight on how the optimal EV design should be altered depending on engineering uncertainty and market heterogeneity.

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