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This study considered the dynamic equilibrium decision-making problem in a three-level supply chain comprising a manufacturer, a recycler and an echelon utilization (EchU) enterprise under the condition of cost-sharing coordination.

This study constructed a differential game model based on cost-sharing coordinated decision-making among a manufacturer, a recycler and an EchU enterprise operating under a cost subsidy. The study determined the optimal equilibrium strategies and evolutionary characteristics of subsidy mechanisms in a closed-loop supply chain. Finally, this study numerically simulated the path evolution process of vehicle battery EchU, the profit of each stakeholder and the sensitivity of parameters and verified the influences of various parameters on the overall structure and path.

The results show that a cost subsidy policy has a moderating effect on the EchU decision-making process and supply chain profit. The effect of that policy increases over time.

This study determined the equilibrium decision-making of enterprises in a closed-loop vehicle battery supply chain from a dynamic perspective, as well as the combined effects of government subsidy policies and cost-sharing coordination mechanisms.

The results have important guiding significance for coordination and cooperation between enterprises in closed-loop supply chains, for their decision-making and for the development of government subsidies.

This study considered the effects of government subsidies on closed-loop supply chains and the introduction of an EchU market to a closed-loop vehicle battery supply chain.

The operation state of lithium-ion battery for vehicle is unknown and the remaining life is uncertain. In order to improve the performance of battery state prediction, in this paper, a joint estimation method of state of charge (SOC) and state of health (SOH) for lithium-ion batteries based on multi-scale theory is designed.

In this paper, a joint estimation method of SOC and SOH for lithium-ion batteries based on multi-scale theory is designed. The venin equivalent circuit model and fast static calibration method are used to fit the relationship between open-circuit voltage and SOC, and the resistance and capacitance parameters in the model are identified based on exponential fitting method. A battery capacity model for SOH estimation is established. A multi-time scale EKF filtering algorithm is used to estimate the SOC and SOH of lithium-ion batteries.

The SOC and SOH changes in dynamic operation of lithium-ion batteries are accurately predicted so that batteries can be recycled more effectively in the whole vehicle process.

A joint estimation method of SOC and SOH for lithium-ion batteries based on multi-scale theory is accurately predicted and can be recycled more effectively in the whole vehicle process.

Appropriate disposal of end-of-life (EOL) electric vehicle battery (EVB) requires new method of supply chain management (SCM) toward sustainability. Sustainable supply chain finance (SSCF) is an innovative managerial practice dedicated to release cash flow pressure and improve operational efficiency in supply chain, which has drawn increasing attentions from academia and industry. There has been few researches on the integration of EOL EVB management and SSCF yet. The paper aims to fulfill this research gap and lead to the conjunction of environmental management with economic and social concerns.

The paper conducts a systematic literature review to discuss the probable SSCF adoption on potential market of EOL EVB disposal.

The results indicate unsustainable factors and potentials to be explored in current market of EOL EVB disposal. As a solution of sustainable SCM, SSCF can ease the tension between the urgent need of EOL EVB disposal and financing problems in the supply chain, strengthening competitive advantages of EV industry.

The significance of this paper lies in offering an interdisciplinary view by drawing upon key perspectives from the emerging sustainable technology of EVB disposal and its underlying battery second use (B2U) market considering SSCF.

Batteries installed on electric vehicles (EVs) should normally be removed when their capacity falls to 70-80 per cent, but they are still usable for other purposes, such as energy storage. This paper studies an EV battery closed-loop supply chain (CLSC) consisting of a battery manufacturer and a remanufacturer. The manufacturer produces new batteries by using natural resources, while the remanufacturer collects returned batteries and makes decisions based on the return quality, that is, to reuse or recycle. The purpose of this paper is to maximise the individual profits through optimising the amount of manufacturing and remanufacturing, respectively, and optimising the purchase price of returned batteries.

Based on the Nash equilibrium, this paper develops a three-period model in the CLSC. In period 1, batteries are made from raw materials; in period 2, returned batteries from period 1 are sorted into low quality and high quality. Some high-quality returns can be reused for other purposes while those non-reusable returns are recycled into materials. In period 3, all the returns are recycled into materials. The analytical results are derived.

The result of the analyses suggest that first, among the variables that affect the (re-)manufacturing decision, the purchase price for returned batteries plays a critical role. In particular, the price of low-quality returns has more influence than the price of high quality returns. Second, the higher purchase price for re-usable returns does not necessarily lead to a higher return rate of reusable returns. Third, the manufacturer’s profit is normally higher than the remanufacturer’s. This suggests the need to design incentives to promote the remanufacturing sector. And finaly, although it is appreciated that maximising the utilisation of batteries over the life-cycle would benefit the environment, the economic benefit needs further investigation.

Although the CLSC has been widely studied, studies on the EV battery CLSC are scarce. The EV battery CLSC is particularly challenging in terms of the reusability of returns because used EV batteries cannot be reused for the original purpose, which complicates CLSC operations. This paper explores the interrelationship between manufacturer and remanufacturer, explaining the reasons why recycling is still underdeveloped, and suggests the possibility of enhancing remanufacturing profitability.

The paper concludes with showing that in the most optimistic scenario, end-of-life (EOL) batteries will account for 86% of energy storage for wind and 36% for solar PV in 2040.

With the growing demand for electric vehicles (EVs), the stock of discarded batteries will increase dramatically if no action is taken for their reuse or recycling. One potential avenue is to reuse them as energy storage systems (ESS) to mitigate the intermittent generation of renewable energy such as solar PV and wind. In a sense, the reliability for solar PV and wind energy can increase if energy storage systems become economically more attractive, making solar and wind systems more attractive through economies of scale.

The paper concludes with showing that in the most optimistic scenario, EOL batteries will account for 86% of energy storage for wind and 36% for solar PV in 2040.

The projection of scenarios can contribute to the information of policies, standards and identification of environmental promotion and promotion related to efficient management for EOL batteries.

Recycling and reuse of the electric vehicle (EV) batteries are ways to extend their limited lives. If batteries can be traced from production to recycling, it is beneficial for battery recycling and reuse. Using blockchain technology to build a smart EV battery reverse supply chain can solve the difficulties of lack of trust and data. The purpose of this study is to discuss the behavioural evolution of a smart EV battery reverse supply chain under government supervision.

This study adopts evolutionary game theory to examine the decision-making behaviours of the government, EV manufacturers with recycled used batteries and third-party EV battery recyclers lacking professional recycling qualification.

On the smart reverse supply chain integrated by blockchain technology, a cooperative recycling strategy of the third-party EV battery recycler is the optimal choice when the government tends to actively regulate. The probability of the EV manufacturer choosing the blockchain adoption strategy exceeds (below) the threshold, and the government prefers negative (positive) supervision. According to numerical analysis, in the mature stage in the EV battery recycling industry, when the investment cost of applying blockchain is high, EV manufacturers' willingness to apply blockchain slows down, the government accelerates adopting a negative supervision strategy and third-party EV battery recyclers prefer cooperative recycling.

The results of this study provide opinions on the strength of government supervision and the conditions under which EV manufacturers and third-party EV battery recyclers should apply blockchain and cooperate. On the other hand, this study provides theoretical analysis for promoting the application of blockchain technology in smart reverse supply chain.

Compared with previous research, this study reveals the relevance of government supervision, blockchain application and cooperation strategy in smart EV battery reverse supply chain. In the initial stage, even if the subsidy (subsidy reduction rate) and penalty are high and the penalty reduction rate is low, the EV manufacturer should rather give up the application of blockchain technology. In the middle stage in the EV battery recycling industry, the government can set a lower subsidy (subsidy reduction rate) combined with a penalty or a higher penalty (penalty reduction rate) combined with a subsidy to supervise it. The third-party EV battery recycler is advised to cooperate with the EV manufacturer when the subsidy is low or the penalty is high.

With the UK’s accelerating plans to transition to electric mobility, this paper aims to highlight the need for policies to prepare for appropriate management of electric vehicle (EV) lithium-ion batteries (LIBs) as they reach the end of their life.

This is a regulatory review based on projections of EV LIBs coming off the market and associated problems of waste management together with the development of a servitisation model.

Circular economy in EV LIBs is unlikely to shape itself because LIB recycling is challenging and still in development. LIB volumes are insufficient for recycling to be currently profitable, and a circular economy here will need to be driven by regulatory intervention. Ignoring the problem carries potentially high environmental and health costs. This paper offers potential solutions through new EV ownership models to facilitate a circular economy.

The authors suggest a new EV ownership model. However, despite environmental benefits, re-shaping the fundamentals of market economies can have disruptive effects on current markets. Therefore, further exploration of this topic is needed. Also, the data presented is based on future projections of EV markets, battery lifespan, etc., which are uncertain at present. These are to be taken as estimates only.

The paper proposes regulatory interventions or incentives to fundamentally change consumer ideas of property ownership for EVs, so that EV automotive batteries remain the property of the manufacturer even when the consumer owns the car.

This aims to illustrate the role robotic technology is playing in the key sectors of the green economy.

Following a short introduction, this paper discusses existing and potential robotic applications in three key sectors of green economy: renewable energy, recycling and waste management and sustainable transport. This is followed by a discussion and concluding comments.

Robots are playing critical and growing roles in each of the three sectors of the green economy considered. Uses are expanding in the production of renewable energy systems and in their inspection and maintenance. Advances in AI and machine vision have enabled robotic mixed waste sorting which plays a vital role in recycling, and the robotic disassembly of electronic products is also gaining pace. Robots are being used extensively in the sustainable transport sector in the manufacture of electric vehicles and also in the production and recycling of electric vehicle batteries. Emerging applications include robotic vehicle recharging and battery swapping.

This provides an insight into the many ways in which robots are contributing to key sectors of the green economy.

To foster the grid integration of both electric vehicles (EV) and renewable generators, the purpose of this paper is to investigate the possible synergies between these players so as to jointly improve the production predictability while ensuring a green mobility. It is here achieved by the mean of a grid commitment over the overall power produced by a collaborative system which here gathers a photovoltaic (PV) plant with an EV fleet. The scope of the present contribution is to investigate the conditions to make the most of such an association, mainly regarding to the management strategies and optimal sizing, taking into account forecast errors on PV production.

To evaluate the collaboration added value, several concerns are aggregated into a primary energy criterion: the commitment compliance, the power spillage, the vehicle charging, the user mobility and the battery aging. Variations of these costs are computed over a range of EV fleet size. Moreover, the influence of the charging strategy is specifically investigated throughout the comparison of three managements: a simple rule of thumb, a perfect knowledge deterministic case and a charging strategy computed by stochastic dynamic programming. The latter is based on an original modeling of the production forecast error. This methodology is carried out to assess the collaboration added value for two operators’ points of view: a virtual power plant (VPP) and a balance responsible party (BRP).

From the perspective of a BRP, the added value of PV-EV collaboration for the energy system has been evidenced in any situation even when the charging strategy is very simple. On the other hand, for the case of a VPP operator, the coupling between the optimal sizing and the management strategy is highlighted.

A co-optimization of the sizing and the management of a PV-EV collaborative system is introduced and the influence of the management strategy on the collaboration added value has been investigated. This gave rise to the presentation and implementation of an original modeling tool of the PV production forecast error. Finally, to widen the scope of application, two different business models have been tackled and compared.