Search results

Filters

  • Journals
  • Authors
  • Keywords
  • Date
  • Type

Search results

Number of results: 3
items per page: 25 50 75
Sort by:
Download PDF Download RIS Download Bibtex

Abstract

The presented article consists of two studies (correlation and experimental) on the importance of self-esteem for the perceived value added by a brand to a consumer’s self-image. Both studies were conducted online, using the snowball method, controlling for participants’ gender and product categories. The correlation study showed that consumers, with an increase in self-esteem understood as a trait, look for more positive traits in brands and fewer negative traits to incorporate into their self-image by purchasing the brand. In addition, they confirmed that brand preference is mainly related to the qualities possessed, which the consumer can confirm by purchasing the brand. The experimental study showed that people with lowered self-esteem perceive more positive traits in brands that they can incorporate into their self-image by purchasing the brand, and there were no differences in confirming positive traits and avoiding negative traits that are associated with the brand. The new measurement of the perceived value of a brand to a consumer’s self- image, used, allowed the identification of specific areas of brand image sensitive to a consumer’s self-esteem.
Go to article

Authors and Affiliations

Paweł Krasa
1
ORCID: ORCID
Oleg Gorbaniuk
2 3
ORCID: ORCID
Magdalena Kolańska-Stronka
4
ORCID: ORCID
Karolina Czarnecka
4
Kinga Czyż
1
Tomasz Karski
1
Agnieszka Krajewska
Paweł Pamuła
1
Dajana Synowiec
1

  1. John Paul II Catholic University of Lublin, Lublin, Poland
  2. Institute of Psychology, Maria Curie-Skłodowska University, Lublin, Poland
  3. Casimir Pulaski University of Radom, Radom, Poland
  4. University of Zielona Gora, Zielona Gora, Poland
Download PDF Download RIS Download Bibtex

Abstract

Temperature rise of the hub motor in distributed drive electric vehicles (DDEVs) under long-time and overload operating conditions brings parameter drift and degrades the performance of the motor. A novel online parameter identification method based on improved teaching-learning-based optimization (ITLBO) is proposed to estimate the stator resistance, ��-axis inductance, ��-axis inductance, and flux linkage of the hub motor with respect to temperature rise. The effect of temperature rise on the stator resistance, ��-axis inductance, ��-axis inductance, and magnetic flux linkage is analysed. The hub motor parameters are identified offline. The proposed ITLBO algorithm is introduced to estimate the parameters online. The Gaussian perturbation function is employed to optimize the TLBO algorithm and improve the identification speed and accuracy. The mechanisms of group learning and low-ranking elimination are established. After that, the proposed ITLBO algorithm for parameter identification is employed to identify the hub motor parameters online on the test bench. Compared with other parameter identification algorithms, both simulation and experimental results show the proposed ITLBO algorithm has rapid convergence and a higher convergence precision, by which the robustness of the algorithm is effectively verified. Keywords: parameters identification, teaching–learning-based optimization, hub motor, temperature rise.
Go to article

Authors and Affiliations

Yong Li
1
Juan Wang
2
Taohua Zhang
2
Han Hu
1
Hao Wu
1

  1. Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China
  2. Beijing Institute of Space Launch Technology, Beijing 100076, China
Download PDF Download RIS Download Bibtex

Abstract

The paper presents a modified algorithm for choosing the optimal coefficient of the share of cogeneration in district heating systems taking into account additional benefits concerning the promotion of highefficiency cogeneration and biomass cofiring. The optimal coefficient of the share of cogeneration depends first of all on the share of the heat required for preparing the hot tap water. The final result of investigations is an empirical equation describing the influence of the ratio of the heat flux for the production of hot tap water to the maximum flux for space heating and ventilation, as well as the share of chemical energy of biomass in the fuel mixture on the optimal value of the share of cogeneration in district heating systems. The approach presented in the paper may be applied both in back-pressure combined heat and power (CHP) plants and in extraction-condensing CHP plants.

Go to article

Authors and Affiliations

Andrzej Ziębik
Paweł Gładysz

This page uses 'cookies'. Learn more