scholarly journals Analysis of Lithium Battery Recycling System of New Energy Vehicles under Low Carbon Background

2020 ◽  
Vol 514 ◽  
pp. 032008
Author(s):  
Zhe Wang
Keyword(s):  
Lithium Battery ◽  
Low Carbon ◽  
Recycling System ◽  
Battery Recycling ◽  
New Energy ◽  
New Energy Vehicles

scholarly journals Economic research and suggestions on the recycling of waste power batteries for China’s new energy vehicles

2020 ◽  
Vol 165 ◽  
pp. 01028
Author(s):  
Li Zhenbiao ◽  
Li Yuke ◽  
Pan Wei ◽  
Wang Jia
Keyword(s):  
Economic Research ◽  
Hydrometallurgical Process ◽  
Analysis Model ◽  
Rare Metals ◽  
Recycling Industry ◽  
Battery Recycling ◽  
Power Battery ◽  
New Energy ◽  
The Cost ◽  
New Energy Vehicles

With the rapid promotion of the number of China’s new energy vehicles in promotion and application, it is of great significance to ensure the recycling of the waste power batteries. It can not only effectively reduce the safety and environmental protection risks brought by the waste power battery, but also alleviate China’s dependence on rare metals such as cobalt and lithium, which has been widely concerned by the industry. In this paper, the cost analysis model of waste power battery treated by hydrometallurgical process is established, and the economy of recycling of ternary material battery and LFP battery is compared and analysed, and the overall economy of the whole power battery recycling industry is analysed, and the relevant conclusions are obtained, and the relevant suggestions of recycling of power battery are put forward according to the analysis results, to provide reference for industry and related management departments.

scholarly journals The Evolution and Determinants of Interorganizational Coinvention Networks in New Energy Vehicles: Evidence from Shenzhen, China

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Jia Liu ◽  
Zhaohui Chong ◽  
Shijian Lu
Keyword(s):  
Knowledge Exchange ◽  
Graph Model ◽  
Low Carbon ◽  
Health Issues ◽  
Random Graph Model ◽  
Exponential Random Graph ◽  
Collaborative Innovation ◽  
New Energy ◽  
Invention Patent ◽  
New Energy Vehicles

With the increasing attention to climate change, air pollution, and related public health issues, China’s new energy vehicles (NEVs) industry has developed rapidly. However, few studies investigated the evolution of interorganizational collaborative innovation networks in the sector domain of NEVs and the influence of different drivers on the establishment of innovation relationships. In this context, this paper uses the joint invention patent of Shenzhen, a low-carbon pilot city of China, to investigate the dynamics of network influencing factors. The social network analysis shows that the scale of coinvention network of NEVs is constantly increasing, which is featured with diversified cooperative entities, and collaboration depth (i.e., the intensity of the interactions with these partners) is also expanding. The empirical results from the Exponential Random Graph Model (ERGM) demonstrate that, with the deepening of collaborative innovation, technological upgrading caused by knowledge exchange makes organizations in the network more inclined to cognitive proximity and less dependent on geographical proximity. In addition, organizational proximity and triadic closure contribute positively to the collaborative network, with their relevance remaining nearly the same, while the impeding effect of cultural/language difference is slightly decreasing with time.

scholarly journals Transfer-Based Deep Neural Network for Fault Diagnosis of New Energy Vehicles

2021 ◽  
Vol 9 ◽  
Author(s):  
Yuping Wang ◽  
Weidong Li
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Deep Neural Network ◽  
Short Term Memory ◽  
Rolling Bearing ◽  
Low Carbon ◽  
Training Time ◽  
Energy Applications ◽  
New Energy ◽  
New Energy Vehicles

New energy vehicles are crucial for low carbon applications of renewable energy and energy storage, while effective fault diagnostics of their rolling bearings is vital to ensure the vehicle’s safe and effective operations. To achieve satisfactory rolling bearing fault diagnosis of the new energy vehicle, a transfer-based deep neural network (DNN-TL) is proposed in this study by combining the benefits of both deep learning (DL) and transfer learning (TL). Specifically, by first constructing the convolutional neural networks (CNNs) and long short-term memory (LSTM) to preprocess vibration signals of new energy vehicles, the fault-related preliminary features could be extracted efficiently. Then, a grid search method called step heapsort is designed to optimize the hyperparameters of the constructed model. Afterward, both feature-based and model-based TLs are developed for the fault condition classifications transfer. Illustrative results show that the proposed DNN-TL method is able to recognize different faults accurately and robustly. Besides, the training time is significantly reduced to only 18s, while the accuracy is still over 95%. Due to the data-driven nature, the proposed DNN-TL could be applied to diagnose faults of new energy vehicles, further benefitting low carbon energy applications.

scholarly journals Research on Chinese New Energy Vehicles Based on Ecological View

2020 ◽  
Vol 179 ◽  
pp. 01026
Author(s):  
Xiaohui Su ◽  
Kaining Meng ◽  
Di Liu
Keyword(s):  
Ecological Environment ◽  
Xi Jinping ◽  
Existing Problems ◽  
Building Technology ◽  
Battery Recycling ◽  
New Energy ◽  
Ecological View ◽  
New Energy Vehicle ◽  
General Secretary ◽  
New Energy Vehicles

This article studies and discusses the existing problems and future development of Chinese new energy vehicles from the perspective of ecological view proposed by General Secretary Xi Jinping. Through data collection and data analysis, this paper summarizes the current problems of short-range mileage, difficult battery recycling, and environmental pollution caused by the current domestic new energy vehicles. Improve domestic new energy vehicle companies from three aspects: car building technology, battery recycling, and service experience, protect the ecological environment, increase economic competitiveness, and promote sustainable economic and social development.

INCENTIVE POLICIES TO ADDRESS CLIMATE CHANGE IN CHINA

2012 ◽  
Vol 09 (04) ◽  
pp. 1250031 ◽  
Author(s):  
JUN JIN ◽  
YING DONG ◽  
JIN CHEN
Keyword(s):  
Climate Change ◽  
Energy Industry ◽  
Low Carbon ◽  
Address Climate Change ◽  
Catching Up ◽  
The World ◽  
New Energy ◽  
Incentive Policies ◽  
New Energy Vehicle ◽  
New Energy Vehicles

China has launched a set of policies and projects to address climate change, one of the most serious problems in the world. This paper reviews the Chinese policies and national plans on the encouragement of environmentally beneficial and energy-saving innovations. Policies on the energy industry and the development of new energy vehicle industry are taken as cases to illustrate in detail the Chinese policies on climate change. The research reveals that actions on the low carbon innovation, such as the innovation on new energy vehicles, not only benefit the dealing with climate change, but also contribute to the strategies of catching up advanced countries.

scholarly journals Supply-Chain Pricing and Coordination for New Energy Vehicles Considering Heterogeneity in Consumers’ Low Carbon Preference

2020 ◽  
Vol 12 (4) ◽  
pp. 1306 ◽  
Author(s):  
Bengang Gong ◽  
Xuan Xia ◽  
Jinshi Cheng
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Marginal Effect ◽  
Low Carbon ◽  
Green Consumers ◽  
Decentralized Decision Making ◽  
New Energy ◽  
Total Profit ◽  
The Impact ◽  
New Energy Vehicles

Given consumers’ willingness to pay different prices for new energy vehicles (NEVs) and traditional vehicles, we construct a utility model of ordinary and green consumers. We establish pricing game models for centralized and decentralized decisions in an NEV’s supply chain in order to study the impact of changes in consumers’ low carbon preference heterogeneity on supply chain pricing and member profit. The results show that consumers’ low carbon preferences and the ratio of green consumers increases with the ex-factory and selling prices of NEVs. An increase in the percentage of green consumers under centralized decision-making will reduce the total profit of the supply chain. Manufacturers’ profits under decentralized decision-making are greater than the dealers’ profits, and the sum of the two members’ profits under decentralized decision-making is less than the total profit of the supply chain under centralized decision-making. We design a revenue-sharing contract to eliminate the double marginal effect.

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