Deciphering business ecosystem capabilities of the emerging electric vehicle industry

Author(s):  
T. Shang ◽  
F. Chang ◽  
Y. Shi
2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Zheng Ma ◽  
Kristoffer Christensen ◽  
Bo Nørregaard Jørgensen

AbstractDue to the complexity of business ecosystems, the architecture of business ecosystems has not been well discussed in the literature, and modeling or simulation of business ecosystems has been rarely focused. Therefore, this paper proposes a business ecosystem ontology and introduces a methodology for business ecosystem architecture design. The proposed methodology includes five stages: 1) Boundary identification of a business ecosystem; 2) Identification of actors and their roles in the business ecosystem; 3) Identification of actors’ value propositions; 4) Identification of interaction between actors; 5) Verification of business ecosystem architecture design. This paper uses the Danish electricity system as an example to introduce the methodology, and use Electric Vehicle home charging as a case study to demonstrate the application of the developed methodology. The case study demonstrates that the proposed methodology is a systematic approach and can be easily applied to any ecosystem architecture design with the five stages, and the designed ecosystem architecture can represent the physical system and business. Several definitions are clarified in the paper, e.g., actor, role, interaction, ecosystem roadmap and expanded/shifted ecosystem, etc. With clear definitions, the proposed methodology provides a visualized, clear structure of behaviors and specifications for a given business ecosystem.


2020 ◽  
Vol 64 (1-4) ◽  
pp. 431-438
Author(s):  
Jian Liu ◽  
Lihui Wang ◽  
Zhengqi Tian

The nonlinearity of the electric vehicle DC charging equipment and the complexity of the charging environment lead to the complex and changeable DC charging signal of the electric vehicle. It is urgent to study the distortion signal recognition method suitable for the electric vehicle DC charging. Focusing on the characteristics of fundamental and ripple in DC charging signal, the Kalman filter algorithm is used to establish the matrix model, and the state variable method is introduced into the filter algorithm to track the parameter state, and the amplitude and phase of the fundamental waves and each secondary ripple are identified; In view of the time-varying characteristics of the unsteady and abrupt signal in the DC charging signal, the stratification and threshold parameters of the wavelet transform are corrected, and a multi-resolution method is established to identify and separate the unsteady and abrupt signals. Identification method of DC charging distortion signal of electric vehicle based on Kalman/modified wavelet transform is used to decompose and identify the signal characteristics of the whole charging process. Experiment results demonstrate that the algorithm can accurately identify ripple, sudden change and unsteady wave during charging. It has higher signal to noise ratio and lower mean root mean square error.


2017 ◽  
pp. 58-76 ◽  
Author(s):  
A. Karpov

The paper considers the modern university as an economic growth driver within the University 3.0 concept (education, research, and commercialization of knowledge). It demonstrates how the University 3.0 is becoming the basis for global competitiveness of national economies and international alliances, and how its business ecosystem generates new fast-growing industries, advanced technology markets and cost-efficient administrative territories.


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