Application of a Pheromone-Based Bees Algorithm as an Optimizer Within a Multidisciplinary Design Optimization System for Powertrain Component Sizing and Control Parameters for Hybrid E-Vehicles
V. T. Long,
M. S. Packianather
Issue:
Volume 1, Issue 1, December 2015
Pages:
1-9
Received:
29 January 2016
Accepted:
8 February 2016
Published:
26 February 2016
DOI:
10.11648/j.ijtet.20150101.11
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Views:
Abstract: This paper presents a Multidisciplinary Design Optimization (MDO) to optimize key component sizes and control strategy for a hybrid electric vehicle, Honda Insight 2000. A pheromone-based Bees Algorithm (PBA), where the food foraging behavior of honey bees combined with evolutionary computation, is used as an optimizer within a MDO system. The PBA uses pheromones, chemical substances secreted by bees and other insects into their environment, enabling them to communicate with other members of their own species. The values of the key component size and control strategy parameters are adjusted according to PBA to obtain the minimization of Fuel Consumption (FC) while dynamic performances have to satisfy the Partnership for a New Generation of Vehicles (PNGV) constraints. In this research, ADVISOR software has been used as the simulation tool, where driving cycles, FTP and HWFET are employed to evaluate FC and dynamic performances. Following a description of the MDO system, the paper shows the results obtained for only the control strategy parameter optimization and the simultaneous optimization of key component sizes and control strategy parameters for the Honda Insight 2000. The results demonstrate the effectiveness of PBA when it is used as the optimizer within a MDO system for determining the optimal parameters of component sizes and control strategy resulting in the reduction of FC and improvement of vehicle performances. In this research, the new version, PBA, showed an improvement of about 20-25% over the Basic Bees Algorithm (BBA) in convergence speed with the nearly same results of optimization targets.
Abstract: This paper presents a Multidisciplinary Design Optimization (MDO) to optimize key component sizes and control strategy for a hybrid electric vehicle, Honda Insight 2000. A pheromone-based Bees Algorithm (PBA), where the food foraging behavior of honey bees combined with evolutionary computation, is used as an optimizer within a MDO system. The PBA ...
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Applying Multithreading for Multi-Rotors with FlyMaple
Nguyen Anh Quang,
Ngo Khanh Hieu
Issue:
Volume 1, Issue 1, December 2015
Pages:
10-14
Received:
29 January 2016
Accepted:
13 February 2016
Published:
11 March 2016
DOI:
10.11648/j.ijtet.20150101.12
Downloads:
Views:
Abstract: With the development of science and technology, the control boards nowadays not only have a higher working clock rate but also supports multithreading. Like the effects of the multithreading processor with the development of computer sciences, control boards supporting multithread is promised to change the world of Unmanned Vehicles. This article focuses on the application of multithread for multi-rotors, a new section which has been recently researched by many universities and developers in the world. After an overview about multithread and the related projects, this article will present the utilization of multithread with FlyMaple, a new generation of control board which has some important advantages comparing to the older generations.
Abstract: With the development of science and technology, the control boards nowadays not only have a higher working clock rate but also supports multithreading. Like the effects of the multithreading processor with the development of computer sciences, control boards supporting multithread is promised to change the world of Unmanned Vehicles. This article f...
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