Battery Suppliers Research Articles

The Impacts of the US Inflation Reduction Act on EV Supply Chains

The Inflation Reduction Act (IRA) passed by the United States in 2022 affected the global layout of electric vehicle (EV) supply chains. This paper explores the impacts of the IRA on the decisions of overseas battery suppliers and domestic EV manufacturers in the US. The main findings are that (1) the suppliers’ and manufacturers’ optimal decisions depend on the local subsidy, tariff, and battery R&D costs: tariffs (subsidies) reduce (increase) the battery R&D level for overseas (local) suppliers, EV prices, and supply chain members’ profits; (2) subsidies and tariffs are key factors in distinguishing manufacturers from overseas procurement and local procurement when R&D cost coefficients are determined; cost coefficients and service fees are the key factors for manufacturers to choose local procurement or R&D cooperation strategies; and (3) when local supply chains compete with overseas supply chains, subsidies will give the local supply chains a sales advantage while giving overseas supply chains a price advantage, and when local supply chains compete with cooperative supply chains, subsidies will give local supply chains a price disadvantage and a sales disadvantage.

Cooperative Recycling Strategy for Electric Vehicle Batteries Considering Blockchain Technology

The rapid growth of new energy vehicle has led to an urgent need for efficiently recycling used power batteries. In addition, battery suppliers can adopt blockchain technology to enhance efficiency in recycling. This article constructs a closed-loop supply chain (CLSC) consisting of a power battery supplier, a new energy vehicle manufacturer, and a third-party recycler, and studies the optimal collaborative recycling mode considering blockchain adoption and recycling competition. Firstly, we identify five alliance recycling models and derive the equilibrium results for each model. Secondly, we use the Shapley value mechanism in cooperative game to allocate alliance profits reasonably. Some interesting conclusions are obtained. (1) The supplier-manufacturer alliance is the optimal recycling strategy under moderate recycling competition, which challenges the common assumption that the major-alliance dominates others in CLSC. (2) Alliances, especially manufacturer-3rd party alliance, are not always beneficial to the CLSC, but are beneficial under low recycling competition and blockchain cost. (3) The proposed four stable profit allocation cases can coordinate the CLSC, where all alliance members achieve higher profits than the decentralized model, with the supplier gaining the largest profit share and the manufacturer obtaining the most profit increment.

Sustainable reputation of lithium-ion battery supplier and its impact on transaction equilibrium in the electric vehicle supply chain

Sustainable reputation of lithium-ion battery supplier and its impact on transaction equilibrium in the electric vehicle supply chain

Electric Vehicle Battery Supply Strategy Considering Brand Spillover Effect

Electric vehicle manufacturers ensure power battery supply through either direct sourcing or technology cooperation. This paper examines the battery supply strategy of an entrant manufacturer(m2), in a two-tier supply chain that includes a battery supplier (s), an incumbent manufacturer (m1), and the aforementioned entrant. It investigates these strategies under the influence of the brand spillover effect. It reveals that when m1 opts for direct battery procurement, if m2 boasts higher after-sales service standards, adopting a technology cooperation strategy becomes more advantageous. A sweet spot exists wherein, given m2's brand power and after-sales service level fall within a certain range, all supply chain participants can achieve mutual benefits. In scenarios where m1 depends on technology cooperation for its battery supply, it is advisable for m2 to mirror this approach by also engaging in technology cooperation.

Cooperation and Production Strategy of Power Battery for New Energy Vehicles Under Carbon Cap-and-Trade Policy

Considering the supply chain composed of a power battery supplier and a new energy vehicle manufacturer, under the carbon cap-and-trade policy, this paper studies the different cooperation modes between the manufacturer and the supplier as well as their strategies for green technology and power battery production. Three game models are constructed and solved, respectively, under the collaboration mode of wholesale purchasing, patent-licensed manufacturing, and own R&D + Wholesale purchasing. The equilibrium analysis is carried out. Finally, the influence of relevant parameters is explored through numerical simulation. It is found that (1) the manufacturer’s choice of optimal battery production strategy is influenced by the input cost of green technology, the production cost of power battery, the carbon trading price, and the free carbon quota allocated by the government; (2) the cost coefficient of technological innovation affects negatively the optimal decision-making of the supply chain members, the market demand, and the optimal profit, and it has no impact when the cost coefficient reaches a certain value; (3) carbon cap-and-trade policy can, to a certain extent, incentivize suppliers and manufacturers to carry out technological innovation to reduce carbon emissions in the production process, but we cannot ignore the negative impacts of excessively high carbon trading price on the level of emission reduction and the market demand; and (4) the government should reasonably control the carbon price and carbon quota. The above conclusion will provide reference suggestions for new energy vehicle manufacturers and related suppliers.

A Relative Projection-Based Multiattribute Group Decision-Making Model With Noncooperative Behavior Management and Application to NEV Supplier Selection.

This article reports a novel consensus model where a group of internal and external experts evaluate alternatives under multiple attributes and provide mutual evaluations. First, different from previous studies, the cognitive and interest conflicts of internal and external experts are considered simultaneously. But interest conflict is emphasized for internal experts, and cognitive conflict is mainly considered for external experts. Second, we explore the categorization and management methods of noncooperative behaviors (NCBs) of experts. The relative projection-based indexes are proposed for the first time to measure the degrees of cognitive and interest conflicts by using multiattribute preference matrices (MAPMs) and the weight vectors of attributes. A group of experts are divided into three categories and the corresponding management strategies are developed. Third, we investigate the consensus mechanism among experts with cognitive and interest conflicts. For reaching an acceptable consensus level, an adjustment process is proposed to revise some local entries in MAPMs and mutual evaluation matrix (MEM). A penalty mechanism is further established to dynamically update the weights of experts. An algorithm is designed to capture the consensus reaching process in multiattribute group decision making, where internal and external experts are distinguished by proposing a parameter. Finally, the high-performance battery supplier selection of new energy vehicle is studied to illustrate the proposed model. The results reveal that the efficiency of reaching consensus can be enhanced by using the developed model with effective management of NCBs.

Supply Chain Coordination of New Energy Vehicles under a Novel Shareholding Strategy

As important methods of ecofriendly transportation, the supply chain coordination of new energy vehicles (NEVs) is an important issue in the field of sustainability. This study constructs a Stackelberg game composed of a power battery supplier and an NEV manufacturer. To better describe the coordination relationship in the NEV supply chain, we introduce the Nash bargaining framework into the fairness concern preference utility function. Through a comprehensive discussion of shareholding ratios and external environment factors, we discover that the traditional shareholding strategy fails to coordinate the NEV supply chain effectively, as enterprises seek to avoid losing management control, which occurs when excessive shares are held by others. In this context, this study proposes a novel industry–university–research (IUR) shareholding strategy, which can more easily achieve supply chain coordination and improve social welfare. In particular, this study reveals the superiority of the novel strategy in eliminating the double-marginal effect caused by high fairness concern preference among NEV enterprises. Based on these facts, we provide enterprises with optimal strategies under different conditions and offer a government-optimal subsidy to maximize the social welfare function.

Study on the Selection of Recycling Strategies for the Echelon Utilization of Electric Vehicle Batteries under the Carbon Trading Policy

Global climate change has prompted all sectors of society to take urgent action to reduce carbon emissions. Electric vehicles are the key to low-carbon transportation transformation, but their popularity has led to difficulties in disposing of used batteries. Improper handling will pollute the environment and violate the original goal of promoting low-carbon practices. Therefore, it is crucial to establish a sustainable battery-recycling and disposal system. This study uniquely incorporates the concept of battery echelon utilization into its analytical framework using a Stackelberg game model, exploring the equilibrium strategies for stakeholders in a closed-loop supply chain under carbon emission constraints. We analyzed the impact of multiple factors in the recycling process, as well as the influence of digital technology, on enterprise pricing, recycling efficiency, and the choice of recycling channels. The study found that the market pricing of batteries and electric vehicles is not influenced by recycling participants, but is instead related to the application of digital technology. Numerical simulations further reveal that the battery’s echelon utilization rate and carbon emission limit policies jointly motivate enterprises to be more proactive in recycling. In the joint recycling model, battery suppliers can achieve more substantial profit growth compared to electric vehicle manufacturers, providing new insights and directions for innovation and the development of collaborative models within the supply chain.

Research on Vertical Cooperation and Pricing Strategy of Electric Vehicle Supply Chain

To determine a vertical cooperation strategy and address the optimal pricing problem of the electric vehicle (EV) supply chain, a supply chain system consisting of two competing EV manufacturers (M1 and M2) and a battery supplier is studied. Firstly, three cooperation strategy models were constructed for the battery supplier and the EV manufacturers, namely: Strategy N (neither the battery supplier nor the two manufacturers cooperate with each other); Strategy I (M1 cooperates with the battery supplier); and Strategy II (M2 cooperates with the battery supplier). Then, the Stackelberg solution method was used to obtain the optimal equilibrium decisions under the three strategic models. Finally, the effect of the preference coefficient of consumers for leasing EVs per unit on the optimal equilibrium decision was analyzed. We found that: (1) The wholesale price of batteries provided by the battery supplier to M1 is always greater than to M2. (2) Strategies I and II prompt M1 and M2 to reduce the unit and fixed rental prices of EVs to some extent, while intensifying the competition between the two manufacturers in terms of EV lease prices. (3) When the consumer preference coefficient (θ) for leasing EVs per unit provided by manufacturer M1 is relatively small, the cooperation alliance S2 and the supply chain achieve the maximum profit under Strategy II; however, while θ is large, M1, cooperative alliance S1, and the entire supply chain could benefit the most under Strategy I.

Two-stage consensus reaching process in social network large group decision-making with application to battery supplier selection

Trust relationships play an important role in social network large group decision making (SN-LGDM). Extant studies overlook the self-adjustment stage of decision makers (DMs) and the binding force of subgroup on preference adjustment in consensus reaching process (CRP). This article proposes a new two-stage CRP for SN-LGDM considering self-adjustment and binding force of subgroup. A new trust propagation approach is presented based on individual trust level. An improved grey clustering algorithm is devised based on the fusion of preference similarity and trust relationship. The preference stability and the awareness of big picture are defined to determine the weights of DMs. The subgroup size, cohesion and influence are integrated to determine the weights of subgroups comprehensively. For the new two-stage CRP, the first stage is self-adjustment stage. DMs may proactively choose to adjust the preference or update the trust relationship according to the degree of matching between the trust relationship and preference difference. In the second stage, four scenarios are identified and the corresponding adjustment strategies are given considering the intention of DM to modify and the binding force of subgroup, which makes the consensus more consistent with reality. A battery supplier selection case is offered to illustrate the proposed method.

A new energy vehicle battery supplier selection using SWARA-MEREC-MARCOS approach under probabilistic triangular intuitionistic hesitant fuzzy environment

In this manuscript, we construct a Multi-Criteria Decision-Making (MCDM) model to study the new energy vehicle (NEV) battery supplier selection problem. Firstly, we select criteria to build an evaluation index system. Secondly, SAWARA and MEREC methods are used to calculate subjective and objective weights in the ranking process, respectively, and PTIHFS (Probabilistic Triangular Intuitionistic Hesitant Fuzzy Set) is employed to describe the decision maker’s accurate preferences in performing the calculation of subjective weights. Then, the game theory is used to find the satisfactory weights. We use TFNs to describe the original information in the MARCOS method to obtain the optimal alternative. Finally, a correlation calculation using Spearman coefficients is carried out to compare with existing methods and prove the model’s validity.

Research on the trade-in modes for electric vehicle power batteries under deposit and fund policies

Abstract Recycling power batteries has gained attention as electric vehicles (EVs) develop rapidly. Government deposit and fund policies encourage battery recycling and cascade utilization. Thus, we construct six trade-in modes for battery supplier, EV manufacturer, and external recycler as recycle entity under deposit and fund policies. Supply chain member profits, battery recycling rate, environmental impact, and social welfare are compared between modes. The results are as follows: (1) Deposit policy has a greater battery recycling rate and lower environmental impact than fund policy, so the best trade-in mode is with the EV manufacturer as recycling entity; (2) Battery supplier and EV manufacturer gain more from the fund policy when recycling themselves, whereas external recycler prefers the deposit policy; (3) Battery supplier recycling under ‘high deposit-high subsidy’ is more likely to promote social welfare, while EV manufacturer recycling under ‘high deposit-low subsidy’ will help the government balance revenue and expenditure.

Basic uncertainty information hesitant fuzzy multi-attribute decision-making method with credibility

This study addresses the inadequacy of the current quantitative calculation method for decision-maker credibility in hesitant fuzzy multi-attribute decision-making, where credibility is considered. To overcome this limitation, a novel quantitative calculation method for decision-maker credibility is proposed based on the principles of basic uncertainty information theory under a hesitant fuzzy environment. Furthermore, a credible-based hesitant fuzzy multi-attribute decision model is developed. Initially, the paper introduces the concept of a basic uncertainty hesitant fuzzy set by combining basic uncertainty information theory with hesitant fuzzy set theory, thereby enhancing the understanding of basic uncertainty information theory within the realm of non-interval fuzzy information. Building on this foundation, the method for determining the hesitant degree of each element in the basic uncertainty hesitant fuzzy set is provided, followed by the proposed quantitative calculation method for decision-maker’s credibility under the hesitant fuzzy environment, which addresses the lack of a quantitative approach for assessing expert credibility under such circumstances. Subsequently, an attribute weight assignment method is introduced, considering the decision-maker’s credibility, leading to the formulation of a basic uncertainty hesitant fuzzy multi-attribute decision model based on credibility. This model enhances existing hesitant fuzzy multi-attribute decision-making methods that take credibility into account. To validate the proposed approach, the study applies it to the selection of new energy vehicle battery suppliers. The results of the analysis using actual data and sensitivity analysis demonstrate that decision-maker credibility can be quantitatively determined using the proposed method. Additionally, the basic uncertainty hesitant fuzzy multi-attribute decision-making model based on credibility effectively aids in supplier selection. The feasibility and stability of this method are verified through the examination of risk appetite coefficient and hesitancy coefficient.

Comparative analysis of fuzzy multi-criteria decision making methods for selecting sustainable battery suppliers of battery swapping station

ABSTRACT Sustainable battery supplier (SBS) selection of battery-swapping station belongs to a complex multi-criteria decision-making (MCDM) problem due to the fact that included multiple and often conflicting criteria. To this end, this study presents a comparative analysis of selecting SBS using four fuzzy MCDM methods, and a case is executed to compare the ranking results obtained by the proposed four MCDM methods. From the weighting results of criteria, it is observed that economic criteria is the first priority in all evaluation criteria, followed by the technical, social, and environmental criteria in descending order. In terms of the priorities and recommendations of multiple SBSs for the battery swapping station, the comparative analysis demonstrates that the rankings of all alternatives obtained by all approaches are in high agreement, except that determined by fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) slightly varies from the other three approaches, and none of these MCDM methods are deemed to be absolutely “perfect”. If possible, we recommend that more than one method should be applied to the same problem to provide a more comprehensive decision basis. If not possible, it is suggested to use the fuzzy VIKOR since it shows more superior potential in sustainable supplier decision analysis.

Supplier development or supplier integration? Equilibrium analysis in competing electric vehicle supply chains with power battery recycling

This paper explores the interaction of supplier development and supplier integration in competing electric vehicle (EV) supply chains with power battery recycling, each composing of one electric vehicle manufacturer (EVM) and one power battery supplier (PBS) who recycles the retired batteries. Each EVM purchases batteries from the PBS of itself and determines whether to integrate with its PBS as well as how much to invest in its PBS to cut battery cost, while the PBS decides the recycling rate. It is shown that after integration the EVM with less capability would reduce investment on supplier development and its PBS would decrease the recycling rate when the heterogeneity of EVMs’ supplier development capabilities (HSDCs) is large enough and EVM with more capability integrates its PBS; otherwise, an EVM would increase investment on supplier development and its PBS would raise the recycling rate after integrating with its PBS. It is also shown that the EVM with more capability always integrates with its PBS, while whether the EVM with less capability integrates with its PBS depends on the HSDCs and the value of echelon use of the retired batteries. Finally, it is shown that (1) the higher the value of echelon use is, the better the environment is; (2) if both EVMs do not integrate with their PBSs, the environment would become better.

Elfly Selects Battery Supplier

Elfly Selects Battery Supplier

Time-series based multi-criteria large-scale group decision making with intuitionistic fuzzy information and application to multi-period battery supplier selection

Battery is the core component of new energy vehicles. The choice of proper battery supplier is crucial for new energy vehicle companies since it directly affects the market share and core competitiveness. Some criteria of battery suppliers cannot be evaluated in the short period and need to be continuously evaluated at different periods (or time). Decision makers (DMs) may present some hesitancy when giving their evaluations. Thus, this paper formulates the battery supplier selection as a type of time-series based multi-criteria large-scale group decision making (LSGDM) with intuitionistic fuzzy information. A novel method is proposed to effectively resolve the battery supplier selection. Firstly, considering the importance of different periods, the comprehensive time weights are determined by combining the exponential decay model and the maximal entropy ordered weighted averaging (OWA) operator weights determining model. Secondly, DMs are divided into different clusters by using the proposed intuitionistic fuzzy Hamming distance-based fuzzy c-means (FCM) algorithm on each criterion. Combining the confidence levels of DMs and the corresponding clustering results, the DMs’ weights with respect to each criterion are determined. Then, the comprehensive criteria weights are obtained by integrating the intuitionistic fuzzy entropy and the constructed multi-objective programming model. Thirdly, the individual consensus level and group consensus degree at each period are defined, respectively. Then, a new identification approach is proposed to identify DMs to be adjusted. Subsequently, a total adjustment minimization model is built to adjust these DMs’ evaluation information. The optimal alternative is generated according to the collective global overall evaluations. Finally, a real example of batter supplier selection is demonstrated to verify the feasibility and superiority of the proposed method.

Exponential information measures-driven Pythagorean fuzzy MADM method and its application to new energy battery supplier evaluation problem

Under the Pythagorean fuzzy environment, this paper presents a multi-attribute decision-making (MADM) model based on exponential entropy measure and exponential similarity measure to evaluate new energy battery supplier’s performance. In this method, the notion of Pythagorean fuzzy linguistic sets (PFLSs) is first introduced by combining the linguistic fuzzy sets (LFSs) and the Pythagorean fuzzy sets (PFSs). Then, the axiomatic definitions of Pythagorean fuzzy entropy and Pythagorean fuzzy similarity measure are developed to measure the degree of uncertainty and similarity between two Pythagorean fuzzy linguistic values (PFLVs). The PFLVs can be expressed by the linguistic membership degree (LMD) and linguistic non-membership degree (LNMD). In addition, we construct two new information measure formulas based on exponential function. Through a series of proofs, we verify that they satisfy the axiomatic conditions of entropy and similarity measure of Pythagorean fuzzy language respectively. On this basis, we research the relationship between the two information measures. Finally, we present a novel Pythagorean fuzzy linguistic MADM model. An example for evaluating performance of new energy battery supplier is given to explain the effectiveness of the newly-developed approach. The stability and validity of the newly-developed approach is performed by sensitivity analysis and comparative analysis.

Sourcing diversification: Strategy selection, sourcing allocation and brand power

The supply of power batteries is monopolised by a few suppliers, resulting in high purchasing costs for electric vehicle manufacturers (EVMs). Hence, some EVMs have implemented diversified sourcing strategies to seek purchase concessions and reduce their dependence on battery suppliers. Motivated by the sourcing strategies of EVMs, we develop a game-theoretic model to investigate the optimal procurement strategies of manufacturers with different brand power. The model consists of a primary supplier, an alternative supplier, and two competing manufacturers, wherein the focal manufacturer has the option of implementing dual sourcing or partial outsourcing through sourcing allocation, whereas the rival manufacturer only sources from the primary supplier. Specifically, we first study the focal manufacturer’s three procurement strategies under the primary supplier’s uniform pricing: single sourcing (the benchmark), dual sourcing and partial outsourcing. Then, we examine the primary supplier’s strategic response to the manufacturer’s sourcing diversification: maintaining uniform pricing or switching to differential pricing. By analysing the equilibrium profits, we find that compared with the situation under single sourcing, both the primary supplier and the focal manufacturer may obtain higher profits under dual sourcing or partial outsourcing. However, with an increase in the focal manufacturer’s order proportion, the primary supplier’s profit may decrease; and the focal manufacturer’s diversified sourcing strategy may hurt all the supply chain players. Furthermore, we show that when the primary supplier considers switching to differential pricing, the focal manufacturer tends to abandon the diversified sourcing and adopt single sourcing.

How Do the Criteria Affect Sustainable Supplier Evaluation? - A Case Study Using Multi-Criteria Decision Analysis Methods in a Fuzzy Environment

Choosing a battery supplier is a vital decision-making problem, for which it is essential to obtain stable evaluations. For such sustainable supplier evaluation, multi-criteria decision analysis (MCDA) methods are often used, as their ability to handle uncertain data gives experts more significant opportunities to consider a broader range of cases. However, given the great number of MCDA approaches, it is challenging to find out which approach is the most appropriate. Therefore, this paper presents a sensitivity analysis on evaluating battery suppliers by ARAS, EDAS, MAIRCA, TOPSIS, and VIKOR methods in a fuzzy environment. The provided study presented similar results for the considered MCDA methods confirmed by the WS similarity measure of rankings and the weighted Spearman correlation . On the other hand, the sensitivity analysis conducted on the considered methods indicated that the most relevant criteria for this problem are transportation cost, delivery time, and warranty period.