Optimization of the Complex-RFM optimization algorithm

Persson, Johanna; Ölvander, Johan

doi:10.1007/s11081-014-9247-9

Cited by 5 publications

(3 citation statements)

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“…A GA with 40 individuals and 40 generations means 1600 function evaluations. A complex optimization can often find a solution in 100–200 evaluations (Persson & Ölvander, 2015). Kriging usually performs better than polynomials as global SMs (Jin et al, 2003).…”

Section: Compared Methodsmentioning

confidence: 99%

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How to compare performance of robust design optimization algorithms, including a novel method

Persson

Ölvander

2017

AIEDAM

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This paper proposes a method to compare the performances of different methods for robust design optimization of computationally demanding models. Its intended usage is to help the engineer to choose the optimization approach when faced with a robust optimization problem. This paper demonstrates the usage of the method to find the most appropriate robust design optimization method to solve an engineering problem. Five robust design optimization methods, including a novel method, are compared in the demonstration of the comparison method. Four of the five compared methods involve surrogate models to reduce the computational cost of performing robust design optimization. The five methods are used to optimize several mathematical functions that should be similar to the engineering problem. The methods are then used to optimize the engineering problem to confirm that the most suitable optimization method was identified. The performance metrics used are the mean value and standard deviation of the robust optimum as well as an index that combines the required number of simulations of the original model with the accuracy of the obtained solution. These measures represent the accuracy, robustness, and efficiency of the compared methods. The results of the comparison show that sequential robust optimization is the method with the best balance between accuracy and number of function evaluations. This is confirmed by the optimizations of the engineering problem. The comparison also shows that the novel method is better than its predecessor is.

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Section: Compared Methodsmentioning

confidence: 99%

“…The engineering problem that the best RDO method should be found for is the electrical motorcycle model presented by Persson and Ö lvander (2015). It is implemented in MATLAB Simulink and consists of models of the battery, electrical motor, gear box, and the motorcycle itself.…”

Section: Engineering Problemmentioning

confidence: 99%

How to compare performance of robust design optimization algorithms, including a novel method

Persson

Ölvander

2017

AIEDAM

Self Cite

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“…[114], for which a number of approaches are listed for example in [115,116]). Here, the Entropy-Rate-Based Performance Index (ERI) [115] is used, which is based on Shannon's [117] information theory.…”

Section: Optimization Performance Evaluationmentioning

confidence: 99%

Simulation-Based Optimization of a Series Hydraulic Hybrid Vehicle

Bær¹

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"The brick walls are there for a reason. (...) [They] are there to give us a chance to show how badly we want something. Randy Pausch AbstractHybrid transmissions are characterized by their utilization of more than one form of energy storage. They have the potential to help reduce overall fuel consumption and vehicle emissions by providing the possibility of brake energy recuperation and prime mover operation management. Electric hybrids and electric vehicle drives are nowadays ubiquitous, and mechanical energy storage in flywheel has been investigated in the past. The use of fluid power technology with a combustion engine has also been investigated since the late 1970s, and is frequently revisited.Hydraulic hybridization is especially attractive for heavy vehicles with frequent braking and acceleration which benefit most from fluid power components' high power density, typically busses, delivery or refuse vehicles, and vehicles with existing hydraulic circuits and transmissions, such as forest and construction machinery, but have been considered for smaller vehicles as well.Due to the characteristic discharge profile of hydraulic energy storage, special attention needs to be paid to control aspects in the design process to guarantee drivability of the vehicle. In this respect, simulation models can be of use in early design process stages for cheaper and faster evaluation of concepts and designs than physical experiments and prototyping, and to generate better understanding of the system studied. Engineering optimization aids in the systematic exploration of a given design space, to determine limits and potentials, evaluate trade-offs and potentially find unexpected solutions. In the optimization of a hydraulic hybrid transmission, the integration of component and controller design is of importance, and different strategies (sequential, iterative, bi-level and simultaneous approaches) are conceivable, with varying consequences for the implementation.This thesis establishes a simulation-based optimization framework for a hydraulic hybrid transmission with series architecture. Component and control parameter optimization are addressed simultaneously, using a rule-based supervisory control strategy. The forward-facing dynamic simulation model at the centre of the framework is built in Hopsan, a multi-disciplinary open-source tool developed at Linköping University. The optimization is set up and conducted for an example application of an on-road light-duty truck over standard drive i cycles. Both results from these experiments as well as the framework itself are studied and evaluated. Relevant design aspects, such as explicit design relations to be considered and performance requirements for more robust design, are identified and addressed, and the optimization problem is analysed with regard to algorithm performance and problem formulation. The final result is an optimization framework that can be adjusted for further in-depth studies, for example through the inclusion of additional components or optimization obj...

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