LI, Feng ;QIN, Yumo ;PANG, Zhao ;TIAN, Lei ;ZENG, Xiaohua . Design and Optimization of PSD Housing Using a MIGA-NLPQL Hybrid Strategy Based on a Surrogate Model. Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 60, n.7-8, p. 525-535, june 2018. ISSN 0039-2480. Available at: <https://www.sv-jme.eu/sl/article/design-and-optimization-of-psd-housing-using-a-miga-nlpql-hybrid-strategy-based-on-a-surrogate-model/>. Date accessed: 10 dec. 2024. doi:http://dx.doi.org/10.5545/sv-jme.2013.1492.
Li, F., Qin, Y., Pang, Z., Tian, L., & Zeng, X. (2014). Design and Optimization of PSD Housing Using a MIGA-NLPQL Hybrid Strategy Based on a Surrogate Model. Strojniški vestnik - Journal of Mechanical Engineering, 60(7-8), 525-535. doi:http://dx.doi.org/10.5545/sv-jme.2013.1492
@article{sv-jmesv-jme.2013.1492, author = {Feng Li and Yumo Qin and Zhao Pang and Lei Tian and Xiaohua Zeng}, title = {Design and Optimization of PSD Housing Using a MIGA-NLPQL Hybrid Strategy Based on a Surrogate Model}, journal = {Strojniški vestnik - Journal of Mechanical Engineering}, volume = {60}, number = {7-8}, year = {2014}, keywords = {HEV, Power-split device, Hybrid optimization, Surrogate model, MIGA, NLPQL}, abstract = {A new power-split device (PSD) is designed as the core component of the multi-power coupling system in a hybrid electric vehicle. It is important to consider the influence of the factors of weight and stiffness on performance of PSD when designing PSD housing. In this paper, the overall arrangement of the power distribution system and PSD housing are redesigned. The finite element analysis is conducted to test PSD housing stiffness. According to the results of the analysis, this study adopts a hybrid optimization strategy based on surrogate models to obtain the least weight under the constraint of PSD housing stiffness. The surrogate models are established using a responsive surface method based on the data obtained by the optimal Latin hypercube design (OLHD). The hybrid optimization strategy combines a multi-island genetic algorithm (MIGA) with a nonlinear programming quadratic line search (NLPQL), which ensures obtaining optimal design parameters for PSD housing. In comparison with optimization using a single MIGA, this hybrid optimization strategy is more efficient and feasible for optimizing housing.}, issn = {0039-2480}, pages = {525-535}, doi = {10.5545/sv-jme.2013.1492}, url = {https://www.sv-jme.eu/sl/article/design-and-optimization-of-psd-housing-using-a-miga-nlpql-hybrid-strategy-based-on-a-surrogate-model/} }
Li, F.,Qin, Y.,Pang, Z.,Tian, L.,Zeng, X. 2014 June 60. Design and Optimization of PSD Housing Using a MIGA-NLPQL Hybrid Strategy Based on a Surrogate Model. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 60:7-8
%A Li, Feng %A Qin, Yumo %A Pang, Zhao %A Tian, Lei %A Zeng, Xiaohua %D 2014 %T Design and Optimization of PSD Housing Using a MIGA-NLPQL Hybrid Strategy Based on a Surrogate Model %B 2014 %9 HEV, Power-split device, Hybrid optimization, Surrogate model, MIGA, NLPQL %! Design and Optimization of PSD Housing Using a MIGA-NLPQL Hybrid Strategy Based on a Surrogate Model %K HEV, Power-split device, Hybrid optimization, Surrogate model, MIGA, NLPQL %X A new power-split device (PSD) is designed as the core component of the multi-power coupling system in a hybrid electric vehicle. It is important to consider the influence of the factors of weight and stiffness on performance of PSD when designing PSD housing. In this paper, the overall arrangement of the power distribution system and PSD housing are redesigned. The finite element analysis is conducted to test PSD housing stiffness. According to the results of the analysis, this study adopts a hybrid optimization strategy based on surrogate models to obtain the least weight under the constraint of PSD housing stiffness. The surrogate models are established using a responsive surface method based on the data obtained by the optimal Latin hypercube design (OLHD). The hybrid optimization strategy combines a multi-island genetic algorithm (MIGA) with a nonlinear programming quadratic line search (NLPQL), which ensures obtaining optimal design parameters for PSD housing. In comparison with optimization using a single MIGA, this hybrid optimization strategy is more efficient and feasible for optimizing housing. %U https://www.sv-jme.eu/sl/article/design-and-optimization-of-psd-housing-using-a-miga-nlpql-hybrid-strategy-based-on-a-surrogate-model/ %0 Journal Article %R 10.5545/sv-jme.2013.1492 %& 525 %P 11 %J Strojniški vestnik - Journal of Mechanical Engineering %V 60 %N 7-8 %@ 0039-2480 %8 2018-06-28 %7 2018-06-28
Li, Feng, Yumo Qin, Zhao Pang, Lei Tian, & Xiaohua Zeng. "Design and Optimization of PSD Housing Using a MIGA-NLPQL Hybrid Strategy Based on a Surrogate Model." Strojniški vestnik - Journal of Mechanical Engineering [Online], 60.7-8 (2014): 525-535. Web. 10 Dec. 2024
TY - JOUR AU - Li, Feng AU - Qin, Yumo AU - Pang, Zhao AU - Tian, Lei AU - Zeng, Xiaohua PY - 2014 TI - Design and Optimization of PSD Housing Using a MIGA-NLPQL Hybrid Strategy Based on a Surrogate Model JF - Strojniški vestnik - Journal of Mechanical Engineering DO - 10.5545/sv-jme.2013.1492 KW - HEV, Power-split device, Hybrid optimization, Surrogate model, MIGA, NLPQL N2 - A new power-split device (PSD) is designed as the core component of the multi-power coupling system in a hybrid electric vehicle. It is important to consider the influence of the factors of weight and stiffness on performance of PSD when designing PSD housing. In this paper, the overall arrangement of the power distribution system and PSD housing are redesigned. The finite element analysis is conducted to test PSD housing stiffness. According to the results of the analysis, this study adopts a hybrid optimization strategy based on surrogate models to obtain the least weight under the constraint of PSD housing stiffness. The surrogate models are established using a responsive surface method based on the data obtained by the optimal Latin hypercube design (OLHD). The hybrid optimization strategy combines a multi-island genetic algorithm (MIGA) with a nonlinear programming quadratic line search (NLPQL), which ensures obtaining optimal design parameters for PSD housing. In comparison with optimization using a single MIGA, this hybrid optimization strategy is more efficient and feasible for optimizing housing. UR - https://www.sv-jme.eu/sl/article/design-and-optimization-of-psd-housing-using-a-miga-nlpql-hybrid-strategy-based-on-a-surrogate-model/
@article{{sv-jme}{sv-jme.2013.1492}, author = {Li, F., Qin, Y., Pang, Z., Tian, L., Zeng, X.}, title = {Design and Optimization of PSD Housing Using a MIGA-NLPQL Hybrid Strategy Based on a Surrogate Model}, journal = {Strojniški vestnik - Journal of Mechanical Engineering}, volume = {60}, number = {7-8}, year = {2014}, doi = {10.5545/sv-jme.2013.1492}, url = {https://www.sv-jme.eu/sl/article/design-and-optimization-of-psd-housing-using-a-miga-nlpql-hybrid-strategy-based-on-a-surrogate-model/} }
TY - JOUR AU - Li, Feng AU - Qin, Yumo AU - Pang, Zhao AU - Tian, Lei AU - Zeng, Xiaohua PY - 2018/06/28 TI - Design and Optimization of PSD Housing Using a MIGA-NLPQL Hybrid Strategy Based on a Surrogate Model JF - Strojniški vestnik - Journal of Mechanical Engineering; Vol 60, No 7-8 (2014): Strojniški vestnik - Journal of Mechanical Engineering DO - 10.5545/sv-jme.2013.1492 KW - HEV, Power-split device, Hybrid optimization, Surrogate model, MIGA, NLPQL N2 - A new power-split device (PSD) is designed as the core component of the multi-power coupling system in a hybrid electric vehicle. It is important to consider the influence of the factors of weight and stiffness on performance of PSD when designing PSD housing. In this paper, the overall arrangement of the power distribution system and PSD housing are redesigned. The finite element analysis is conducted to test PSD housing stiffness. According to the results of the analysis, this study adopts a hybrid optimization strategy based on surrogate models to obtain the least weight under the constraint of PSD housing stiffness. The surrogate models are established using a responsive surface method based on the data obtained by the optimal Latin hypercube design (OLHD). The hybrid optimization strategy combines a multi-island genetic algorithm (MIGA) with a nonlinear programming quadratic line search (NLPQL), which ensures obtaining optimal design parameters for PSD housing. In comparison with optimization using a single MIGA, this hybrid optimization strategy is more efficient and feasible for optimizing housing. UR - https://www.sv-jme.eu/sl/article/design-and-optimization-of-psd-housing-using-a-miga-nlpql-hybrid-strategy-based-on-a-surrogate-model/
Li, Feng, Qin, Yumo, Pang, Zhao, Tian, Lei, AND Zeng, Xiaohua. "Design and Optimization of PSD Housing Using a MIGA-NLPQL Hybrid Strategy Based on a Surrogate Model" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 60 Number 7-8 (28 June 2018)
Strojniški vestnik - Journal of Mechanical Engineering 60(2014)7-8, 525-535
© The Authors, CC-BY 4.0 Int. Change in copyright policy from 2022, Jan 1st.
A new power-split device (PSD) is designed as the core component of the multi-power coupling system in a hybrid electric vehicle. It is important to consider the influence of the factors of weight and stiffness on performance of PSD when designing PSD housing. In this paper, the overall arrangement of the power distribution system and PSD housing are redesigned. The finite element analysis is conducted to test PSD housing stiffness. According to the results of the analysis, this study adopts a hybrid optimization strategy based on surrogate models to obtain the least weight under the constraint of PSD housing stiffness. The surrogate models are established using a responsive surface method based on the data obtained by the optimal Latin hypercube design (OLHD). The hybrid optimization strategy combines a multi-island genetic algorithm (MIGA) with a nonlinear programming quadratic line search (NLPQL), which ensures obtaining optimal design parameters for PSD housing. In comparison with optimization using a single MIGA, this hybrid optimization strategy is more efficient and feasible for optimizing housing.