Battery outsourcing decision and product choice strategy of an electric vehicle manufacturer

2020 ◽  
Author(s):  
Zhi‐Ping Fan ◽  
Zhongwei Chen ◽  
Xuan Zhao
Keyword(s):  
Electric Vehicle ◽  
Product Choice ◽  
Vehicle Manufacturer ◽  
Choice Strategy ◽  
Outsourcing Decision

Product Choice Strategy for Online Retailers

2008 ◽  
Vol 4 (1) ◽  
pp. 22-39 ◽  
Author(s):  
Ruiliang Yan ◽  
Amit Bhatnagar
Keyword(s):  
Product Choice ◽  
Choice Strategy ◽  
Online Retailers

scholarly journals TESLA VERTICAL INTEGRATION STRATEGIES: THEORY, PRACTICE, RESULTS

2020 ◽  
Vol 8 (7) ◽  
pp. 184-188
Author(s):  
E. K. Movsesyan ◽  
M. E. Anokhina
Keyword(s):  
Electric Vehicle ◽  
Vertical Integration ◽  
Growth Strategies ◽  
Vehicle Manufacturer ◽  
Turbulent Environment ◽  
Theoretical Part ◽  
Integration Strategies

The purpose of this article is to disclose the content of vertical integration strategies using Tesla as an example. In the theoretical part, the typology of integrated growth strategies is considered, and the feasibility of their application is substantiated. The practical part presents the experience of using such strategies with the Tesla electric vehicle manufacturer in the turbulent environment of the company.

Adaptive identification methods of nonlinear random electrical signal

2020 ◽  
Vol 64 (1-4) ◽  
pp. 431-438
Author(s):  
Jian Liu ◽  
Lihui Wang ◽  
Zhengqi Tian
Keyword(s):  
Wavelet Transform ◽  
Electric Vehicle ◽  
Signal To Noise Ratio ◽  
Sudden Change ◽  
Electrical Signal ◽  
Signal Recognition ◽  
State Variable ◽  
Signal Characteristics ◽  
The Matrix ◽  
Kalman Filter Algorithm

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.

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