Technological direction prediction for battery electric bus under influence of China's new subsidy scheme

Accepted Manuscript Technological direction prediction for battery electric bus under influence of China's new subsidy scheme Jiuyu Du, Minggao Ouyang, Xiaogang Wu, Xiangfeng Meng, Jianqiu Li, Feiqiang Li, Ziyou Song PII:

S0959-6526(19)30654-7

DOI:

https://doi.org/10.1016/j.jclepro.2019.02.249

Reference:

JCLP 15979

To appear in:

Journal of Cleaner Production

Received Date: 4 June 2018 Revised Date:

18 February 2019

Accepted Date: 25 February 2019

Please cite this article as: Du J, Ouyang M, Wu X, Meng X, Li J, Li F, Song Z, Technological direction prediction for battery electric bus under influence of China's new subsidy scheme, Journal of Cleaner Production (2019), doi: https://doi.org/10.1016/j.jclepro.2019.02.249. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT

Technological Direction Prediction for Battery Electric Bus under Influence of China’s New Subsidy Scheme Jiuyu Du1, Minggao Ouyang1, Xiaogang Wu1,2,Xiangfeng Meng3, Jianqiu Li1, Feiqiang Li1*, Ziyou Song1

China

RI PT

1. State Key Laboratory of Automotive Safety and Energy, Tsinghua University, 100084, Beijing,

2. College of Electrical and Electronics Engineering, Harbin University of Science and Technology, 150080, Harbin, China

SC

3. Contemporary Amperex Technology Co.Limited ,352106,Ningde, China

Jiuyu Du; e-mail: [email protected]

M AN U

Corresponding author: Feiqiang Li; e-mail: [email protected] Abstract： ：Battery electric buses (BEBs) play a very important role of reducing urban tailpipe emissions in transportation sector for China. The national strong incentive policies place China at the forefront of the BEBs’ market in the world. However, challenges are even more

TE D

severe owing to the negative effects of national subsidies on the BEBs industry and technologies’ option. The abovementioned problems indicate that the subsidy mechanism is not scientific and systematic. Therefore, this research focus on the comprehensive evaluating method of addressing the inner influencing principle of technological specification mentioned

EP

in new subsidy scheme on the technological development direction of BEBs. The evaluation indicators in the method include cost-benefit and electricity consumption rate and for different

AC C

size BEBs. The scenario of maximum subsidy obtaining target based on the optimal install battery estimation is set up; then, the potential direction of the BEBs market penetration was investigated. The cost-benefit and energy consumption estimating models are set up to examine the economics of all size BEBs and the difference between BEBs and equivalent conventional bus. Furthermore, the potential positive and negative effects of the technological requirements in the subsidy scheme are investigated The results show that normal-charging BEBs, the market for light-duty BEBs will shrink greatly owing to significant reduction in the subsidy amounts. However, the market penetration of 12 m BEB will increase significantly. LFP batteries will dominate the normal-charging heavy-duty BEB market in near and medium term, but NCM–type traction batteries will gradually be dominating the energy storage market

ACCEPTED MANUSCRIPT for normal-charging BEBs owing to increasing demands in terms of the energy density of traction batteries. However, the market penetration of fast-charging-type BEBs will growth more rapidly than ever before due to the great increasing in its cost-benefit.

RI PT

Keywords: battery electric bus; battery specific energy; charge rate; energy consumption rate; fast charge; all electric range Acronyms:

MOT MOF AER MSRP ESS SOC

SC

15 16 17 18 19 20

M AN U

MOST

TE D

14

plug-in electric vehicle Battery electric bus Electric vehicle New energy vehicle Battery electric vehicle plug-in electric bus plug-in electric car Battery electric special vehicle LiFePO4 Li(NiCoMn)O2 Li4Ti5O12 LiMnO2 Ministry of Industry and Information Technology of the People Republic of China Ministry of Science and Technology of the People Republic of China Ministry of Transport of the People's Republic of China Ministry of Finance of the People's Republic of China All electric range for electric vehicle manufacture retailed price energy storage system state of charge

EP

PEV BEB EV NEV BEV PEB PEC BESV LFP NCM LTO LMO MIIT

AC C

1 2 3 4 5 6 7 8 9 10 11 12 13

Nomenclatures:

1 2 3 4

L Ekg ST SN

the length of bus electricity consumption rate for per load mass the total subsidy for BEBs the national subsidy

ACCEPTED MANUSCRIPT

the specific energy of the traction battery for BEBs the rate of maximum charge current the electricity consumption rate the additional mass transported the tested value of electric vehicle-energy consumption

Cep Cbat Cmot Cec Ebat δbat Pmot δmot Pec δec e ηT ηB ηG ms ua SE f i δ g Eb Ebat SOCw SOCmax SOCmin CD A

the cost of the electric powertrain the cost of the traction battery pack the cost of the motor the cost of the motor control unit. the energy stored in an onboard battery pack the specific price of the battery the peak motor power the specific price of motor the power of motor control unit the specific price of motor control unit the energy-consumption rate of the BEB the efficiencies of transmission battery charge/discharge the traction motor system the curb mass of the BEB minus mass of battery pack the speed of bus all-electric range rolling resistance coefficient; gradient resistance coefficient; the conversion coefficient of rotary components gravitational acceleration the effective battery energy for driving total battery energy, respectively the operation window of the battery pack the maximum operation values of the battery the minimum operation values of the battery drag coefficient front area specific energy of the battery pack

M AN U

SC

RI PT

Es r E M Ea

TE D

14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43

γbat_d

the local government subsidy the operational subsidy for a bus the subsidy amount for BEBs the subsidy density the indicator of battery cost discount ratio

EP

10 11 12 13

SL SO S Sd

AC C

5 6 7 8 9

△E

ACCEPTED MANUSCRIPT mc mb ms

the curb mass the mass of the traction battery system BEB mass without battery

RI PT

44 45 46

1. Introduction

The challenges of ensuring energy security and mitigating urban air pollution caused by the

SC

transportation section are becoming more severe for China. To this end, Chinese government taken developing plug-in electric vehicles (PEV) as its strategy to solve the abovementioned problems, however, in China it is also called new energy vehicles (NEV) [1]. Its definition

EP

TE D

M AN U

and classification are shown as Figure.1.

Figure. 1 The classificaton for PEV in Chinese

Many national incentive policies have been introduced to improve the market penetration of

AC C

PEVs, including purchasing subsidy policies since 2009, infrastructure construction subsidy policies, and tax deduction policies. Owing to these policies, the PEV market in China has grown rapidly since 2013.China has been ranking first worldwide in terms of the annual PEV production and ownership with sales of 379,000 units in 2015, surpassing US for the first time [2]. In 2016, the growing trend continued with annual PEVs sales of 500,000 units as shown in Figure 2, meanwhile, the cumulative sales for PEV increased to 900,000 units. Among them, the market growth of plug-in electric bus (PEB) is explosive, in that its annual sales reached 135,400 units. At the same time, the annual sales for buses in Chinese market are 547,000 units, which means the market share of new PEBs is more than 24.7%.

SC

RI PT

ACCEPTED MANUSCRIPT

M AN U

Figure. 2 Industrial progress of PEVs in China

Among the PEB market, the BEB has been taken the most market share as shown as Figure.3. The most important promoting force for the market penetration of BEBs is the powerful subsidy policies of Chinese government [2], and other incentive policies will further improve its market penetration. PEBs’ ownership is expected to stand at 700,000, with the penetration rate being 100% in 2020. As a result, China has been ranking first worldwide in terms of BEB

160000 140000

TE D

ownership and penetration rate.

89.6

120000

Only over10m length BEB eligible for subsidy

75.8

EP

100000

100 85.5 6-9m length BEB eligible for subsidy 79.8

60

57.5

50

48.0

40

60000

AC C

80 70

80000

30

28.2

40000

20

20000

0 2010

90

10 0 2011 PHEB

2012

2013 BEB

2014

2015

2016

Market share of BEB

Figure. 3 Market constitution of BEBs

Although the development of BEBs’ industry is very important for sustainable transportation in China, unrationed fast growth have many negative effects. BEBs are over-subsided and it cause negative influence on the sustainable industrial development. These negative effects

ACCEPTED MANUSCRIPT may reduce the drive for self-innovation among OEMs [3].Therefore, has been argued that the subsidy regulation is not reasonable and effectiveness of it should be evaluated. In the face of the abovementioned problems, the Chinese government issued a new subsidy scheme for 2017 to 2020, aiming to achieve healthy and sustainable development of PEVs, especially for BEBs’ industry. The revised subsidy scheme is expected to be more reasonable

RI PT

and scientific, and it is based on the setting up of a complicated and comprehensive multi-criteria system. The scheme will greatly influence the constitution of the BEB industry and the technology roadmap options for BEBs. In the present study, the positive and negative influence of the new incentive policies for BEBs are discussed at length.

SC

A few studies along similar lines have been conducted, for instance, studies on the influence of customer behavior on market penetration. Hao et al. [4] presented the rationale behind

M AN U

China’s PEV Subsidy 2.0 and estimated its impact on PEV market penetration. They found that technological improvements that reduced the cost of batteries played an important role in spurring the development of China’s PEV market. He et al. [5] proposed an extended norm activation model to study the relationship between personal norms and consumers' intention to adopt EVs, as well as to explore how such a relationship is influenced by external costs and by the antecedents of personal norms. Zhou et al. [6] analyzed trends in the Chinese and the US PEV markets and associated government policies. They found that national and regional

TE D

PEV incentives majorly influence the growth of PEV markets in some countries. Zhang et al. [7] estimated the travel and adoption demands of BEVs in Japan considering diverse consumption attitudes based on three years of global positioning system data of 1.6 million people. They found that increasing purchasing subsidies is more effective than improving

EP

battery capacity for increasing the adoption potential of BEVs. Zhang et al. [8] revealed the mechanism by which various factors influence consumers' EV purchase intentions based on

AC C

an analysis of 264 respondents. The findings may be useful for policymakers to formulate more effective adoption policies. However, if these findings can be integrated with real data, they could be more helpful. Olson et al. [9] proposed the concept of lead markets to explain the global diffusion of new technologies and products, and they examined the PEV lead markets of Norway and California to determine the importance of technology improvements and PEV-supporting public policies for achieving widespread PEV adoption. The method can help evaluate diffusion prospects and support for PEV technology. By using a model that estimates the incremental cost of different PEVs, Contestabile et al. [10] found that a PEV policy with a strong bias toward long-range BEVs can possibly increase the costs of electrification in the medium term, possibly exceeding the ability of governments to sustain the necessary incentives until battery costs drop sufficiently. Liu et al. [11] explored the

ACCEPTED MANUSCRIPT development characteristics of PEVs under policy incentives by using the scenario analysis method. The results indicated that China's PEV market penetration is driven dominantly by national incentive policies, especially financial support, and cutting the financial support will have a direct negative effect on the large-scale market penetration of BEBs. Kieckhäfer et al. [12] used an automotive market simulator (AMaSi) to analyze the leverage of manufacturers to support the market diffusion of EVs. The results indicated that manufacturers' portfolio

RI PT

decisions strongly influence the market development of PEVs. Li et al. [13] used Shenzhen city as a case to analyze the interactions between enterprises and governments along the value chain of PEVs in the contexts of bus and taxi fleets. Additional incentive policies are recommended in the paper. Wang et al. [14] analyzed the factors influencing the NEV

SC

purchase intentions of residents based on an investigation of the situation in seven Chinese geographical regions and 22 provinces. The findings reflect a few consumers' potential purchase demands and are helpful to ensure that subsidies are targeted in a more tangible

M AN U

manner. Silvester et al. [15] found that the sustainable urban development can be made more feasible by cleverly combining renewable energy, electricity grid design, inductive park & charge infrastructure, and customized PEV services.

In addition to the research on interaction of incentive policies and market penetration, researchers also investigated various technologies to improve BEB performance. A few

TE D

studies focused on the energy consumption and GHG emissions of BEBs [16],[17]. Song et al. [18] developed a methodology for cost-optimized planning of charging infrastructure installation and depot charging of BEBs fleets. Xylia et al. [19] developed a dynamic optimization model for installing BEB charging infrastructure, using Stockholm as a case

EP

study. The model identified whether conductive or inductive technology should be used for charging BEBs. Gao et al. [20] developed a framework tool to link bus electrification

AC C

feasibility with real-world vehicle performance, city transit service reliability, battery size, and charging infrastructure. The results indicated that significant benefits could be realized by employing multiple battery configurations and flexible battery swapping practices in electric buses.

Studies in the abovementioned literatures have focused mainly on the influences of EV policies, customer behavior, and manufacturer behavior on the market penetration of EVs. For BEBs, extant studies have focused on hurdles to penetration, optimization of charging infrastructure, energy consumption and GHG emission of BEBs, and cost-benefit analysis of BEBs. However, the incentive policy influencing on powertrains option were scarcely addressed or study deeply.

This is the main motivation of our research. This research begins

ACCEPTED MANUSCRIPT in Section 2 by summary of the BEBs incentive policies in China market, after which the changing in up boundary of fiscal subsidy benefit will be discussed. Section 4 investigated the potential driving force by technological specification requirement of the new subsidy scheme. The subsequent section looks at the projection of BEB pushed by new subsidy scheme from

finding of this research. 2. Overview of incentive policies for BEBs

RI PT

energy consumption rate and cost-benefit views. The final section will summarize the main

SC

BEB ownership is far behind China for other countries owing to the lack of a suitable

operation environment and strong incentive policies. However, the latter plays a determining

M AN U

role in terms of the mass penetration of BEBs for China. 2.1 National overall incentive policies for BEBs

Many incentive policies issued recently, as summarized in Table.1, are expected to provide a further boost to the mass penetration of BEBs. Many other incentive polices have been issued, and they can play a role in promoting the penetration of BEBs. However, subsidy policies

2009–2017

AC C

2015–2019

Table. 1 Main national BEB promotion projects Department Policies Key Content Providing national fiscal subsidy of up to MOF, MIIT, Purchase subsidies 50 RMB/unit for purchasing BEBs [21] MOST [22] [23] [24]. Providing operational subsidy of up to MOF Operational subsidies 80,000 RMB for BEBs based on size [25]. Accelerate the Implementation of New As of 2020, the share of new energy Energy Vehicles in the MOT buses in the bus sector should not be Transportation Industry: lower than 30% [26]. Push NEV penetration in the transportation sector. Assessing regulations for The number of new energy electric buses MOT, MOF, new energy bus must account for 20–60% of new and MIIT demonstration program replacement public buses in 2017 [27]. The share of electric buses in overall "13th Five-Year Plan" of MOT public buses should be greater than 35% urban public transportation by 2020 [28]. "13th Five-Year Plan" The share of electric buses in public Development Plan of State council buses in prefecture-level cities should be Modern Comprehensive no less than 35% by 2020 [29]. Transportation System

EP

Time

TE D

remain the most decisive factor.

2015–2020

2015–2020

2016–2020

2017–2020

ACCEPTED MANUSCRIPT

2.2 Fiscal incentive policies for BEBs

Up to the end of 2017, fiscal incentives for EVs in China can be divided into four phases. The

RI PT

first phase (2009–2012) [21] can be called national subsidy 1.0 and the second phase (2013– 2015) [22] national subsidy 2.0. The third phase refers to subsidies in 2016[23], and it can be called national subsidy 3.0, and the subsidy policy outed in 2017[24] can be called subsidy 4.0. The specifications of the schemes in different phases differ greatly. However, in all schemes,

SC

the subsidy levels are determined based on different BEB classification schemes. Therefore, it is necessary to clarify the classification used for developing subsidy scheme, as is done in the

M AN U

following subsection.

2.3 Technological classification of BEBs for different subsidy schemes In the different phases of subsidy schemes, two classification methods are applied to identify the level of subsidy. One classification method is based on the installed energy storage system(ESS) and the other is based on BEB length. The subsidy policies in different phases summarized in Table 2.

TE D

differ greatly in many respects, such as eligible models and technological specifications, as Table. 2 Subsidy eligibility models for BEBs SP1

SP2

SP3

SP4

2009–2012

2013–2015

2016

2017

EP

Stage

L ≤ 6

Micro duty

6 ≤ L<8

6 ＜ L ≤ 8

6 ＜ L ≤ 8

8 ≤ L < 10

8 ＜ L ≤ 10

8 ＜ L ≤ 10

L ≥ 10

L ≥ 10

L ＞ 10

L ＞ 10

AER required

×

×

√

√

Ekg required

×

×

√

√

Battery performance required

×

×

×

√

Subsidy for fast-charging bus

×

√

√

√

Operational subsidy

×

×

√

√

AC C

Light duty Covering models

Medium duty

Heavy duty

ACCEPTED MANUSCRIPT

In the Chinese national subsidy scheme, BEBs are classified into two categories based on the energy storage system, as summarized in Table 3. One is the normal-charging-type using ordinary-energy-type lithium batteries (including LFP, LMO, NCA, NCM), and the other is

RI PT

the fast-charging-type BEB with power-type energy storage devices, mainly LTO and super-capacitors (SCs). The maximum charging rate of the BEBs in the former category does not exceed 1 C and that for latter necessarily exceeds 3C, even going up to 16 C.

Table. 3 Basic comparison between normal-charging and fast-charging BEBs Fast-charging BEBs

Energy storage device

LFP, NCA, NCM

LTO, SC

AER, km

200–400

≤50

Charging rate, C

≤1C

Charging frequency, times/day

1-2

M AN U

SC

Normal-charging BEBs

≥3C

>5

2.3.1 Overview of fiscal incentive policies for BEBs

TE D

In national subsidy scheme 1.0, only heavy-duty buses with body length greater than 10 m were eligible for subsidy. However, for national subsidy schemes 2.0 (2013–2015), scheme 3.0, and scheme 4.0 for BEBs, two types of BEBs are allocated subsidies of different amounts.

EP

The total subsidy for a BEB can be expressed as follows. S T =S N + S L + S O

(1)

AC C

where ST is the total subsidy for BEBs, SN is national subsidy, SL is local government subsidy, and the SO is the operational subsidy for a bus. The operational subsidy policy has been effective from 2015, therefor the definition of BEBs size is same as SP2 stage, and the subsidy amount for light duty, medium duty and heavy duty BEBs are 40,000, 60,000, and 80,000 Yuan respectively.

2.3.2 Insight into specific schemes

(1) First-phase subsidy policy

ACCEPTED MANUSCRIPT In national subsidy scheme 1.0, the subsidy for normal-charging BEBs with lengths no less than 10 m was set to 500,000 RMB [21], but requirements in terms of the technological specifications of the buses were not specified. Unfortunately, fast-charging BEBs were not included in this scheme.

RI PT

(2) Second-phase subsidy policy The national subsidy scheme 2.0 takes into effect in 2013, as summarized in Table 4. Table. 4 National subsidy scheme for BEBs (2013–2015) [22] Length (m) Light duty

Medium duty

Heavy duty

300

400

500

M AN U

Subsidy (Thousand Yuan)

SC

Model

The specified AER for normal-charging BEBs was required being more than 150 km, but fast-charging BEBs were not required to adhere to this AER specification in this scheme. In addition, in national subsidy scheme 2.0, that is, the 2013–2015 subsidy policy for BEBs [30, 31], the level of subsidy provided in 2013 was to be reduced by 5% and 10% in the years

TE D

2014 and 2015, respectively.

The significant change between this scheme and the previous one was the provision of high levels of subsidies to light- and medium-duty BEBs, which led to the provision of excessive

EP

subsidies.

(3) Third phase subsidy policy

AC C

In the subsidy policy of 2016, the national subsidy for BEBs was determined by the AER and Ekg (defined as electricity consumption rate per load mass) of BEBs, as summarized in Table 5. According to the technological requirements of BEBs, the AER of normal-charging BEBs must be no less than 150 km. BEBs model measuring more than 10 meter in length are assigned as the baseline model. Table. 5 National subsidy scheme for baseline BEB model in 2016 [23] (Thousand Yuan) 10 m ＜ L ≤ 12 m Ekg, Wh/km·kg

R（40 km/h constant speed testing） 6 ≤ R ＜ 20

Ekg < 0.25

220

20 ≤ R ＜ 50

50 ≤ R ＜ 100

100 ≤ R ＜ 150

150 ≤ R ＜ 250

260

300

350

420

R ≥ 250

500

ACCEPTED MANUSCRIPT 0.25 ≤ Ekg < 0.35

200

240

280

320

380

460

0.35 ≤ Ekg < 0.5

180

220

240

280

340

420

0.5 ≤ Ekg < 0.6

160

180

200

250

300

360

0.6 ≤ Ekg < 0.7

120

140

160

200

240

300

RI PT

The 2-D determination indicator method was proposed for defining the national subsidy amount, and the determinants were AER and Ekg. BEBs measuring more than 10 m in length were defined as standard models, and the subsidy coefficient was 1. However, other models have different subsidy coefficients, as listed in Table 6. In the case of BEBs with lengths less

SC

than 6 m, the national subsidy rate is discounted by 80%. The subsidy coefficient is 1.2 for BEBs with lengths greater than 12 m. The 10-m BEB is defined as the baseline model for

M AN U

normal-charging-type BEBs, and for models whose length is less than 6 m, the multiple coefficient is 0.2; moreover, the multiple coefficients are 0.5, 0.8, and 1.2 for light duty, medium-duty, and heavy-duty BEBs, respectively.

Table. 6 National subsidy discount coefficient for BEBs in scheme 3.0 BEB Length L ≤ 6m

Subsidy coefficient

TE D

0.2

0.5

8m ＜ L ≤ 10 m

0.8

10m ＜ L ≤ 12 m

1

L > 12 m or double-decker BEB

1.2

EP

6m ＜ L ≤ 8 m

However, for fast-charging BEBs, the national subsidy for purchasing is 150,000 RMB, and

AC C

no technological specifications are required. More importantly, in SP3, for obtaining subsidy, not only must the technical requirements be met but also the accumulative mileage must exceed 30,000 km [23].

(4) Fourth phase subsidy policy Subsidy scheme 4.0 for BEBs is considerably different, as shown in Table.6. Battery performance is employed as a calculation standard for determining the disbursal of national subsidy. The specific energy density of a battery of a normal-type BEB is specified, and models with high energy density are encouraged based on their multiple coefficients. The purpose of this indicator is to promote the improvement of traction battery technology. The

ACCEPTED MANUSCRIPT charging and discharging rate is added as subsidy criteria for fast-charging type BEBs. A

AC C

EP

TE D

M AN U

SC

RI PT

three-dimensional standards system is set up, as summarized in Table 7.

ACCEPTED MANUSCRIPT

Table. 7 National subsidy scheme for battery electric bus (2017–2020) [24]

BEB

Subsidy standards (thousand RMB/kWh) 1.8

Coefficient

Es (Wh/kg) 85 ≤ Es ≤ 95

95 ≤ Es ≤

Es ＞ 115

115

Fast charge BEB

3.0

1

1.2

charging rate, C

8 ＜ L ≤

8m

10 m

90

M AN U

0.8

6 ＜ L ≤

60

3 ≤ r ≤ 5

5 ≤ r ≤ 15

0.8

1

L ＞ 10 m

SL, thousand RMB

200

300

SL ≤ 0.5SN

120

200

SC

Model

RI PT

Upper boundary for SN, thousand RMB

R ＞ 15

1.4

AC C

EP

TE D

where Es is the specific energy of the traction battery for BEBs; r is the rate of maximum charge current.

ACCEPTED MANUSCRIPT The Ekg of all the models must be no more than 0.24 Wh/km·kg, which is different from the previous policy scheme. In addition, the minimum value of AER has been increased from 150 to 200 km for normal-charging BEBs. Providing deep insights into the influence of scheme 4.0 is the focus of the present study. To

RI PT

this end, the scheme is discussed in the subsequent section. 3. Influence of new national subsidy scheme for BEBs

The market for BEBs is mainly driven and influenced by the national fiscal subsidy scheme.

SC

The influence of this scheme on technology promotion and roadmap options are studied in

M AN U

this section.

3.1 Changes in benefits of BEB models based on new subsidy policy

To find the interaction characteristics between the technical requirement in subsidy scheme and the BEB technologies improvement, the fluctuation of the subsidy volume for the normal-charging BEBs and fast charging BEBs was investigated by the subisidy scheme

1200

SN for Light duty BEB SN for heavy duty total subsidy for medium duty

SN for medium duty BEB total subsidy for light dutty total subsidy for heavy duty

0% decline

800

0% decline

600

AC C

Subsidy,thousand RMB

EP

1000

TE D

transition, as shown in Figure 4 and Figure 5 respectively.

400

200

0 2015

2016

2017

Figure 4 Changes in subsidy for normal-charging-type BEBs

The Figure 4 describe the changing of normal-charging BEBs. In Figure 4, the SN stand for national subsidy. From Figure 4, in 2016, for a normal-charging-type BEB, the subsidy for light-duty BEBs has been decreased by 17%, and the maximum subsidy for medium- and

ACCEPTED MANUSCRIPT heavy-duty BEBs have not changed, except that the threshold AER has been set to more than 250 km. In other words, in the case of BEBs measuring more than 10 m in length must have an AER exceeding 250 km and Ekg not exceeding 0.25 to obtain the same national subsidy as

RI PT

that in the scheme of 2015.

For medium- and heavy-duty BEBs, the subsidy is same as that of previous subsidy only if the conditions of Ekg < 0.25 and AER > 250 km are satisfied simultaneously. For subsidy scheme in 2017, the subsidy volume for light-duty BEBs was decreased by 64% compared

SC

with that of 2016, and BEBs measuring 6 m or shorter in length were made ineligible for national subsidy. The subsidy for medium- and heavy-duty BEBs were increased by 50% and

M AN U

40% respectively. The local subsidy cap was raised for the first time that it must be lower than 50% national subsidy, which means the total subsidy declined greatly. For light-duty BEBs, the total subsidy decreased by 73% compared to that in 2015, and the decreases in subsidy for medium- and heavy-duty BEBs were 63% and 55%, respectively.

The changing characteristics of the subsidy for different size BEBs share shown in Figure.5. All types of fast-charging type BEBs were provided uniform subsidy in 2016, regardless of

TE D

the AER and ESS size, which is different from the subsidy scheme for normal-charging BEBs. In 2017 scheme, the up boundary of the subsidy amount for all kinds of BEBs all reduced compared with that of 2016.

EP

SN for light duty SN for medium duty SN for heavy duty ST for light duty ST for medium duty ST for heavy duty

60 50

AC C

Fiscal subsidy/Thousand Yuan

70

40 30 20 10

0 2015

2016

Figure. 5 Change in subsidy for fast-charging-type BEBs

2017

ACCEPTED MANUSCRIPT

3.2 Changes in technological requirements

In the new scheme, the multi-criteria determination method was proposed for the first time for

RI PT

improving BEB performance, including Ekg, AER, battery mass ratio, specific energy of battery pack for normal-charging BEBs, and charging current rate for fast-charging BEBs. Ekg was defined as electricity consumption rate per load mass, and it can be calculated as follows: (2)

SC

E kg = E M

where E is the electricity consumption rate, and M [33] is the additional mass transported. E =

M AN U

Ea/LAER, where Ea is the tested value of according to GB/T 18386 <>. The value options for M are as follows.

(3)

TE D

  M g -M c if (M g -M c ) ≤ 180  M = 180 if (360 ≤ (M g -M c ) > 180)   M g -M c if (M -M ) > 360 g c  2

The AER threshold for normal-charging BEBs was set to 200 km (as tested at a constant vehicle speed of 40 km/h). In subsidy scheme 4.0, the subsidy volume for BEBs has been

EP

decreased significantly and rigid technical requirements have been set. In near term, these measures may influence market penetration negatively, but in the long term, these measures

AC C

will prove beneficial from the viewpoint of pushing technological improvement. The influence characteristics will be discussed in the following section. 4. Developing potential and inner force for BEB The cost-benefit of purchasing and operating process for BEBs is the most important factor for the acceptance of the market. The price of the battery pack determine the cost-benefit performance of the difference size BEBs under the condition that the subsidy is not considered. However, the cost of battery pack is determined by the battery type and installed capacity. In this section, the typical best sale BEBs models are selected to process the analysis of direct influence by the new subsidy scheme on their cost-benefit. The analysis is performed

ACCEPTED MANUSCRIPT from the energy storage system option, capacity of energy storage system, total subsidy amount, and subsidy density for per unit and pen kWh battery respectively. 4.1 Energy storage system options for BEBs

RI PT

In the new subsidy scheme, battery performance is used as a determining index for energy-type lithium BEBs. However, for fast-charging BEBs, the indicator is maximum charging current rate of the battery (ordinary LTO or super-capacitor).

LFP, NCM, and LTO batteries are the main energy storage systems(ESSs) adopted in BEBs.

SC

Therefore, BEBs with these three types of battery are selected to evaluate the influence of the subsidy on their cost-benefit. For normal-charging-type BEBs, LFP and NCM batteries are

M AN U

the main ESSs, however, for fast-charging-type BEBs, LTO and SC dominant the market. To evaluate the cost-benefits of the different energy storage systems used in BEBs, a cost evaluation model is proposed.

The cost of an electric powertrain comprises the cost of the traction battery system, motor and control units, as follows.

TE D

Cep =Cbat + Cmot + Cec

(4)

where Cep is the cost of the electric powertrain, Cbat is cost of the traction battery pack,

EP

Cmot is cost of the motor, and Cec is cost of the motor control unit. The cost model can alternatively be expressed as follows. (5)

AC C

Cep =Ebat .δ bat + Pmot .δ mot + Pec .δ ec

where Ebat is the energy stored in an onboard battery pack; δbat is specific price of the battery, Pmot is peak motor power, δmot is specific price of motor, Pec is power of motor control unit, and δec is specific price of motor control unit. Under the assumption of obtaining maximum subsidy for all selected BEB models, the top boundary of the installed battery capacity can be obtained. For equivalent BEBs, the electric motor and the electronic control unit are the same. Therefore, the material type, its size, and other battery-related factors determine the cost difference for battery pack. Then, in this study, the change in price owing to the selection of different battery options is examined. The cost

ACCEPTED MANUSCRIPT subsidy deducted for BEBs of different size with different energy storage systems can be calculated using on the cost estimation equation, as shown in Figure.6.

450

140

NCM LFPns LTOns

120

RI PT

400

Battery pack price deducted rate by subsidy%

LFP LTO NCMns

100

350 300

80

250

60

SC

200 150 100 50 0 7m

8m

Figure. 6 Cost-benefit

9m

M AN U

Energy storage system cost/thousand RMB

500

10 m

11 m

40 20 0

12 m

of BEBs with different types of energy storage systems

TE D

Based on the abovementioned analysis, BEBs with the NCM battery are more cost-competitive compared to BEBs with other ESSs after deducting any fiscal subsidies. 4.2 Evaluating and forecasting of different size BEBs

EP

The subsidy volume is calculated based on the installed battery capacity. Therefore, within the upper and lower boundaries, a greater battery capacity is eligible for higher subsidy.

AC C

However, the installation of large batteries is associated with drawbacks such as higher upfront purchase cost and lower energy efficiency. The cost-effectiveness of different types of BEBs models is investigated herein under the assumption that all models can obtain the maximum subsidy. Furthermore, the maximum installed battery capacity determined based on the upper subsidy boundary can be obtained for BEBs models ranging in length from 7 m to 12 m, as shown in Figure 7.

ACCEPTED MANUSCRIPT 500

x=1.0 Top subsidy threshold value x=1.2 Top subsidy threshold value 7m 8m 9m 10 m 11 m

450 400

300 250 200

RI PT

battery capacity /kWh

350

150 100 50 0 6

7

8 9 10 Length of BEB/m

11

12

SC

5

13

M AN U

Figure 7 Installed battery capacity of BEBs

The typical BEB models available in the market were selected for analysis based on the upper boundary value of battery capacity determined by the maximum subsidy. The AERs of those models were 250–300 km, and the specific energies of the corresponding batteries ranged from 95–115 Wh/kg, as listed in Table 8.

7m

260

8m

250

9m

252

10 m

260

11 m

300

12 m

280

Battery energy, kWh

Pmsrp

62.2

124.4

89.1

178.2

162

324

EP

AER, km

AC C

Model

TE D

Table. 8 Performance of evaluated BEB models

147.5

295

193

386

178

356

The MSRP of typical BEB models are shown in Figure 8.

ACCEPTED MANUSCRIPT MSRP SN ST

1400 1200 1000 800 600 400 200 0

8m

9m

10 m

11 m

12 m

SC

7m

RI PT

Price/Subsidy(thousand RMB)

1600

Figure. 8 MSRP of and subsidy for BEBs of different sizes

M AN U

Figure 8 shows the changing in the up boundary subsidy level for BEBs measuring 7 m and 8 m in length. It can be found that the subsidy cannot offset the cost of the battery pack. Considering the three indicators of fiscal subsidy volume, battery cost offset ratio, and fiscal subsidy ratio in the MSRP of BEBs, the cost differences P_diff of all models are shown in Figure 9. The subsidy volumes for the 6– -m long BEB models decrease sharply. However, in case of the 10–12 m long BEB models, the cost-benefit ratio is favorable compared to other

500

140

p_dif SN share of battery cost ST share of battery cost

120

EP

100

300

AC C

pdif/thousand RMB

400

80

200

60

100

40

0

7m

8m

9m

10 m

11 m

12 m

-100

20

-200

0

Figure. 9 The cost difference among BEBs post deduction of subsidy

SN/SL in battery cost/%

600

TE D

BEB models, as shown in Figure.9.

ACCEPTED MANUSCRIPT 4.3 Evaluation based on real market penetration data

This evaluation is based on an analysis of the market penetration characteristics in 2017. The changes in technological specifications from 2016 to 2107 were analyzed to verify the influence of subsidy scheme 4.0. The results of a statistical analysis of the technical

RI PT

specifications in for 2016 and 2017 by MIIT are shown in Figures 10 (a) and (b), respectively. The catalogs released in 2016 and 2017 list

(b)

TE D

(a)

M AN U

SC

1,280 and 89 BEB models, respectively.

Figure. 10 Comparison between BEB parameters in 2016 and 2017

In 2016, of the total number of BEB models, heavy-, medium-, and light-duty BEBs

EP

accounted for 39%, 28%, and 33%, respectively. However, the corresponding values in 2017 changed to 41%, 46%, and 13%. The results show that the models shares of medium- and

AC C

heavy-duty BEBs increased significantly, but that of light-duty BEBs decreased sharply. An examination of the battery technologies used in BEBs based on 2017 data shows that LFP is dominant, as shown in Figure 11. The results can be ascribed not only to the cost-benefit advantages of LFP under the SP4 scheme but also of the mandatory nature of the standard [34]. However, the thermal runaway testing specified in the standard cannot be met by most BEBs with NCM batteries. Therefore, the analysis method and results can be verified only to a partial extent.

M AN U

SC

RI PT

ACCEPTED MANUSCRIPT

Figure. 11 Constitution of battery application for BEBs (2017)

5. Projection of maximum subsidy for various BEB technologies The battery type and installed capacity determines the cost of battery pack as above

TE D

mentioned. Therefore, the type energy storage and maximum battery capacity should be chose and designed rigorously for different size BEBs. In subsidy scheme, the AER is the important required technological indicator, and more AER means higher subsidy. AER is determined by the capacity of the installed battery pack. Charging type and AER are used as indicators to

EP

analyze their influence on the cost-benefit of BEBs. In the last version of the national subsidy scheme, the threshold value of AER for BEBs was 200 km. Therefore, in this study, AERs of

AC C

200, 250, 300, 350, 400 km were selected as scenarios for analysis. 5.1 Energy consumption estimation model The technical parameters of the present typical BEBs can be obtained from the test reports published by MIIIT. However, to examine the influence of subsidy on changes in the parameters, such as AER, Ekg, and installed battery capacity, an energy-consumption estimation model must be set up. The typical BEB models in the market were selected for this purpose, covering the 6 m, 8 m, 10 m, 11 m, and 12 m BEB models. To perform the research, a model for estimating battery capacity should be developed considering AER, component efficiencies, installed battery capacity, and driving cycle as

ACCEPTED MANUSCRIPT shown in Figure.12. The model should be able to evaluate the energy consumption of constant speed driving cycle, additional mass, and system efficiency. The maximum capacity of the installed traction battery system is constrained by the technical requirement that the battery system should account for no more than 20% of the curb mass of the BEB. ms = mc − m b

(6)

model as equation(7).

PEV =

( P +P +P +P ) f

w

i

j

(7)

mc .g. f .ua C . A.ua3 ;Pw is the drag force power, Pw = D ; 3600 76140

mc .g.i.ua du ;Pj is acceleration power, Pj =δ .mc . a . 3600 dt

M AN U

Pi is slope force power, Pi =

η

SC

Pf is the rolling resistance power, Pf =

1

RI PT

The estimation model for battery capacity can be derived from the traditional vehicle dynamic

The driving power is all provided by battery for BEB, therefore the power of battery can be expressed as equation (8).

du  1  mc .g. f .ua CD . A.ua3 mc .g.i.ua + + +δ .mc . a  Pb = PEV =  76140 3600 dt  η  3600 t

du 1  mc .g . f .ua CD . A.ua3 mc .g.i.ua + + +δ .mc . a  76140 3600 dt η  3600 0 t

0

TE D

Eb = ∫ PB .dt = ∫

(8)

 .dt 

(9)

The mass of battery is determined by the installed capacity, energy density and the operation

AC C

EP

windows, therefore it can be calculated by following equation.

mb =

Eb Es .SOCw

(9)

The estimation model for battery capacity is expressed as equation (7) derived by authors.

   Eb   ms +  g Es .SOCw   ua dua  CD Aua3  RE 1 1 1  Eb =  fua + iua + δ + ηT ηB ηG  3600 g dt  76140  ua     

It can also be transformed to equation (8).

(10)

ACCEPTED MANUSCRIPT ms g. f .RE CD . A.ua2 .RE + 3600 76140 Eb = g . f .RE ηT .η B .ηG − 3600.Es .SOCw

(8)

The energy of the battery pack can be estimated by equation (9). EBat = Eb / SOCw

EBat =

RI PT

Further, it can be expressed as equation (10).

(9)

RE .Es ( 423.ms .g. f + 20.CD . A.ua2 )

1522800.ηT .η B .ηG .SOCw .Es − 423.g. f .RE

(10)

SC

Then, the energy-consumption model of BEBs under the constant speed cycle can be obtained as equation (11) based on the abovementioned equations. In addition to the conventional

M AN U

factors, such as, ms, f, and CD.A, energy-consumption rate is mainly determined by the specific energy of the battery, AER, SOC operation window, and efficiency of the electric powertrain.

e=

Es ( 423.ms .g. f + 20.CD . A.ua2 )

1522800.ηT .η B .ηG .SOCw .Es − 423.g . f .RE

(11)

TE D

where e is the energy-consumption rate of the BEB; η is the efficiency of powertrain,

η =η B .ηG .ηT ; ηT , ηB, and ηG are the efficiencies of transmission, battery charge/discharge, and motor system, respectively; ms is the curb mass of the BEB minus mass of battery pack; ua is

EP

the BEB speed; SE is all-electric range; f is rolling resistance coefficient; i is gradient resistance coefficient; δ is the conversion coefficient of rotary components, δ=1.02; g is gravitational acceleration, 9.8m.s-2; Eb and Ebat are the effective battery energy for driving and

AC C

total battery energy, respectively; SOCw is the operation window of the battery pack, where SOCw = SOCmax - SOCmin, which are the minimum and maximum operation values of the battery, respectively; CD is drag coefficient; A is front area; △E is specific energy of the battery pack; mc is curb mass; mb is the mass of the traction battery system; and ms is BEB mass without battery.

SC

RI PT

ACCEPTED MANUSCRIPT

Figure. 12 Flowchart of simulation for determining boundary of traction battery

M AN U

The basis parameters for the simulation are listed in Table 9.

Table 9 Main simulation parameters ms, kg

8

6,210

10

9,648

11

1,0196

12

1,1370

Testing mass, kg

Cd

A，m2

1,500

0.65

6.38

2,300

0.68

7.5

2,400

0.68

7.7

2,600

0.68

7.7

TE D

Length, m

5.2 Analysis of simulation results

EP

Based on the abovementioned energy-consumption model, the upper boundary of the traction battery associated with the maximum subsidy target can be obtained as shown in Figure 13.

AC C

260

Energy up boundary/kWh

240 220 200 180 160 140 120 100

8

10

11 Length(m)

Figure. 13 Upper boundary of installed traction battery

12

ACCEPTED MANUSCRIPT To evaluate the interactions among battery performance, AER, and cost-effectiveness influenced by national subsidy, subsidy density is proposed as an indicator to evaluate the reasonability of the subsidy amount. It is defined as the fiscal subsidy volume per unit capacity of the traction battery system, as expressed by the following equation. Sd =

S Ebat

(12)

RI PT

where S is the subsidy amount for BEBs, and Sd is subsidy density.

The subsidy density for different sized BEBs with normal charging is shown in Figure 14. 4000

battery subsidy per battery subsidy per battery subsidy per battery subsidy per

SC

3000 2500

M AN U

battery subsidy per unit(RMB/kWh)

3500

2000 1500 1000

TE D

500 0

unit(12m) unit(11m) unit(10m) unit(8m)

100

150

200

250 300 AER(km)

350

400

450

Figure. 14 Subsidy per unit battery capacity

EP

Based on the results in Figure 14, the density of the national subsidy is advantageous for

AC C

heavy-duty BEBs, especially for the 11-m-long model, compared to models of other sizes. Furthermore, to perform cost-benefit analysis considering different AERs for differently sized BEBs, the indicator of battery cost discount ratio γbat_d is proposed, as in equation (12).

γ bat_d = S − C bat

(13)

The ratio of the mass of the battery pack to curb mass should be less than 20%. The curb mass of a BEB varies as the battery capacity changes under the assumption that the mass of motor would not change significantly with the battery capacity. Therefore, in the model, different battery capacities influence the curb mass and AER of the BEB, and they can be calculated. The effects of the designed AER on the break-even point of battery cost are shown in Figure

ACCEPTED MANUSCRIPT 15. 400

150 battery capacity(12 m) battery capacitty(11 m) battery capacitty(10 m) battery capacitty(6 m) battery capacitty(8 m) battery cost offset(12m) battery cost offset(11m) battery cost offset(10m) battery cost offset(8m)

50

250

0

difference of battery price vs subsidy/thousand RMB

300

100

RI PT

traction battery installed capacitty/kWh

350

200

-50

150

-100

-150

50

0 150

200

250

300

350

400

M AN U

100

SC

100

-200

-250

450

AER(km)

Figure .15 Effects of designed AER on break-even point of battery cost

Based on Figure 15, from the viewpoint of offsetting additional battery cost, the heavy-duty BEBs offer advantages. Among them, for the 10-m, 11-m, and 12-m models, AERs of 200 km,

6.Conclusions

TE D

300 km, and 250 km, respectively, are optimal.

EP

Based on an analysis of the characteristics of BEB incentive polices and its industrialization progress, to increase BEB penetration, higher subsidies will continue in future. With this in

AC C

mind, to make the subsidy scheme be more scientific and rational policies is very important for sustainable development of the BEB industry. Based on the abovementioned results, by setting up the scenario of obtaining the maximum subsidy, we can conclude that the multi-criteria subsidy scheme has a positive effect on promoting technological improvement of BEBs. However, the challenges still significant. (1) Under the condition that the baseline performance is achieved, obtaining the maximum subsidy will still be the strongest internal motivating force for OEMs. Therefore, the target of safety, energy consumption performance should be carefully designed and converted into the testable indicators to make the incentive policies take into effect. Ekg is a very important indicator to positively influence the improvement of energy efficiency. However, it is

ACCEPTED MANUSCRIPT controversial as well. Therefore, the indicator for energy efficiency should be carefully designed further to conceal eliminate of the model whose Ekg is lowered only by super heavy curb mass. (2) Based on the cost and energy-consumption model, the cost-benefit of BEBs different sizes and equipped with different ESSs were investigated. BEBs of all sizes with NCM batteries

RI PT

were found to have advantages in terms of the subsidy offset cost rate. It is expected that considering multiple technical requirements, such as AER, battery energy density, and

lightweight technologies, the NCM battery is expected to be the main ESS in BEBs from the viewpoint of cost-benefit. Thermal runaway safety will be a core issue for BEBs with NCM

SC

batteries. The new subsidy specification is very favorable to fast-charging BEBs from the viewpoint of cost break-even happen by subsidy, making them more competitive than

M AN U

normal-charging BEBs with LFP.

(3) Suitable AER for different size BEB are investigated. Heavy-duty BEBs are better than light–medium-duty BEBs from the optimal subsidy viewpoint. Further, in the case of normal-charging heavy-duty BEBs, an AER of 200–300 km was found to be optimal from the viewpoint of cost-benefit. For ordinary bus operation route, more than 400 km AER BEB is

cost-benefit.

TE D

expected, therefore, the subsidy scheme should make BEB with AER within this rang more

(4) The motivation of the adding the requirement of energy density for traction battery is to encourage application of the high performance battery and reduce energy consumption rate,

EP

however its negative influence is even significant in safety issue. Based on the analysis results, the using NCM battery will make the BEB more cost-benefit, therefore, only restricted by

AC C

technological requirement by subsidy, the battery roadmap option for BEB will uncertainty and reasonable.

(5)The lightweight technologies requirement is not mentioned directly in the new subsidy scheme, but the tendency to encourage high AER will result in BEB OEMs installing LFP batteries and adopting lightweight materials and processes on a large scale. The influence on BEB powertrain developing direction of this motivation will be very uncertainty in future. (6)The energy consumption rate has of BEB under present constant speed testing condition, has too big difference with that of real operation values, therefore the rated value is misleading for BEBs users. From the viewpoint of BEB technologies improvement, the

ACCEPTED MANUSCRIPT testing driving cycle should be changed from constant speed to the compound cycle, failing which the AER value would be less meaningful. As a next step, the findings of this study must be evaluated using 2018 data to verify and improve. Furthermore, innovative policies for supporting BEB development should be

RI PT

investigated before the national subsidy is phased out.

Acknowledgments

SC

This study is sponsored by the National Natural Science Foundation of China (51877121) and

M AN U

International Science & Technology Cooperation Program of China（2016YFE0102200）, the National Natural Science Foundation of China (71403142). The authors would like to thank the anonymous reviewers for their reviews and comments.

References

AC C

EP

TE D

1.Du J, Ouyang M, Chen J. Prospects for Chinese electric vehicle technologies in 2016-2020: Ambition and rationality. ENERGY. 2017;120:584-596. 2.Du J, Ouyang D. Progress of Chinese electric vehicles industrialization in 2015: A review. APPL ENERG. 2017;188:529-546. 3.MOF. Adjusting and Perfecting the Fiscal Subsidy Policy to Promote the Healthy Development of the New Energy Vehicles. http://jjs.mof.gov.cn/zhengwuxinxi/tongzhigonggao/201612/t20161230_2509421.html. [accessed 17.03.01]. 4.Hao H, Ou X, Du J, Wang H, Ouyang M. China’s electric vehicle subsidy scheme: Rationale and impacts. ENERG POLICY. 2014;73:722-732. 5.He X, Zhan W. How to activate moral norm to adopt electric vehicles in China? An empirical study based on extended norm activation theory. J CLEAN PROD. 2018;172:3546-3556. 6.Zhou Y, Wang M, Hao H, Johnson L, Wang H, Hao H. Plug-in electric vehicle market penetration and incentives: a global review. MITIG ADAPT STRAT GL. 2015;20:777-795. 7.Zhang H, Song X, Xia T, Yuan M, Fan Z, Shibasaki R, et al. Battery electric vehicles in Japan: Human mobile behavior based adoption potential analysis and policy target response. APPL ENERG. 2018;220:527-535. 8.Zhang X, Bai X, Shang J. Is subsidized electric vehicles adoption sustainable: Consumers’ perceptions and motivation toward incentive policies, environmental benefits, and risks. J CLEAN PROD. 2018;192:71-79. 9.Olson EL. Lead market learning in the development and diffusion of electric vehicles. J CLEAN PROD. 2018;172:3279-3288. 10.Contestabile M, Alajaji M, Almubarak B. Will current electric vehicle policy lead to cost-effective electrification of passenger car transport? ENERG POLICY. 2017;110:20-30. 11.Liu D, Xiao B. Exploring the development of electric vehicles under policy incentives: A scenario-based system dynamics model. ENERG POLICY. 2018;120:8-23.

ACCEPTED MANUSCRIPT

AC C

EP

TE D

M AN U

SC

RI PT

12.Kieckhäfer K, Wachter K, Spengler TS. Analyzing manufacturers' impact on green products' market diffusion – the case of electric vehicles. J CLEAN PROD. 2017;162:S11-S25. 13.Li Y, Zhan C, de Jong M, Lukszo Z. Business innovation and government regulation for the promotion of electric vehicle use: lessons from Shenzhen, China. J CLEAN PROD. 2016;134:371-383. 14.Wang Z, Zhao C, Yin J, Zhang B. Purchasing intentions of Chinese citizens on new energy vehicles: How should one respond to current preferential policy? J CLEAN PROD. 2017;161:1000-1010. 15.Silvester S, Beella SK, van Timmeren A, Bauer P, Quist J, van Dijk S. Exploring design scenarios for large-scale implementation of electric vehicles; the Amsterdam Airport Schiphol case. J CLEAN PROD. 2013;48:211-219. 16.Dreier D, Silveira S, Khatiwada D, Fonseca KVO, Nieweglowski R, Schepanski R. Well-to-Wheel analysis of fossil energy use and greenhouse gas emissions for conventional, hybrid-electric and plug-in hybrid-electric city buses in the BRT system in Curitiba, Brazil. Transportation Research Part D: Transport and Environment. 2018;58:122-138. 17.Zhou B, Wu Y, Zhou B, Wang R, Ke W, Zhang S, et al. Real-world performance of battery electric buses and their life-cycle benefits with respect to energy consumption and carbon dioxide emissions. ENERGY. 2016;96:603-613. 18.Song Q, Wang Z, Wu Y, Li J, Yu D, Duan H, et al. Could urban electric public bus really reduce the GHG emissions: A case study in Macau? J CLEAN PROD. 2018;172:2133-2142. 19.Xylia M, Leduc S, Patrizio P, Silveira S, Kraxner F. Developing a dynamic optimization model for electric bus charging infrastructure. Transportation Research Procedia. 2017;27:776-783. 20.Gao Z, Lin Z, LaClair TJ, Liu C, Li J, Birky AK, et al. Battery capacity and recharging needs for electric buses in city transit service. ENERGY. 2017;122:588-600. 21.MOF,MOST.Notice on Launching Pilot Programs for Energy Saving and New Energy Vehicle Demonstration and Promotion. http://www.mof.gov.cn/zhengwuxinxi/caizhengwengao/2009niancaizhengbuwengao/caizhengwengao2009dierqi /200904/t20090413_132178.html. [accessed 17.03.01]. 22.MOF. Notice on continuing new energy vehicles demonstration program; 2013.available from: http://jjs.mof.gov.cn/zhengwuxinxi/tongzhigonggao/201309/t20130916_989833.html.[accessed 17.03.01]. 23.MOF.Notice on the Financial Support Policy for the Promotion and Application of New Energy Vehicles in 2016-2020.http://jjs.mof.gov.cn/zhengwuxinxi/zhengcefagui/201504/t20150429_1224515.html.[accessed 17.03.01]. 24.MOF.Notice on Adjusting Financial Subsidy Policies for Promoting and Applying of New Energy Vehicles.http://jjs.mof.gov.cn/zhengwuxinxi/tongzhigonggao/201612/t20161229_2508628.html.[accessed 17.03.01]. 25.MOF.A Notice on Improving the Oil Price Difference Subsidy Policy for Urban Bus to Promote the Penetration of New Energy Vehicles. http://jjs.mof.gov.cn/zhengwuxinxi /zhengcefagui/201505/t20150514_ 1231726.html. [accessed 17.03.01]. 26.MOT. The implementation Advices of Accelerating the Application of NEVs in the transport industry. [accessed 17.03.01]. 27.MOT. Promotion and Appraisal Measures for Electric Bus (Trial). http://www.mof.gov.cn/mofhome/yunnan /lanmudaohang/zhengcefagui/201609/t20160909_2413911.html. [accessed 17.12.01]. 28.MOT. The Outline of the "13th Five-Year Plan" for Urban Public Transportation . http://www.mot.gov.cn/zhuanti/shisanwujtysfzgh/guihuawenjian/201702/t20170213_2163887.html. [accessed 16.12.01]. 29.China State Council. "13th Five-Year Plan" Development Plan of Modern Integrated Transportation System. http://www.gov.cn/zhengce/content/2017-02/28/content_5171345.htm. [accessed 17.03.01]. 30.Notice on Further Promoting the Market penetration of NEVs. http://jjs.mof.gov.cn/zhengwuxinxi/tongzhigonggao/201402/t20140208_1041234.html. [accessed 17.03.01].

ACCEPTED MANUSCRIPT

AC C

EP

TE D

M AN U

SC

RI PT

31.MOF. Notice on Promoting the Application and Industrialization of the NEVs. http://jjs.mof.gov.cn/zhengwuxinxi/tongzhigonggao/201309/t20130916_989833.html. [accessed 17.03.01] . 32.AQSIQ, SAC. Electric vehicles-Energy consumption and range-Test procedure. In General Administration of Quality Supervision Inspection and Quarantine of the People's Republic of China, Standardization Administration of the People's Republic of China,. GB/T1838-20052005. p.1-7. 33.MIIT. Safety Technological Requirements for Battery Electric Buses. Beijing.2016.P.1-10 34.MIIT. Notice on Further Improving Safety Supervision and Application of New Energy Vehicles. http://www.miit.gov.cn/n1146295/n1652858/n1652930/n3757018/c5362809/content.html. [accessed 17.03.01].

ACCEPTED MANUSCRIPT

Highlights:

The cost-benefit for heavy duty is optimal under new subsidy scheme

RI PT

owing to the higher subsidy density

competitive

SC

Fast charging battery electric buses with LTO battery being

Optimal AER obtained by subsidy maximum oriented battery

M AN U

capacity determination model

Market acceptance for light duty battery electric buses will shrink dramatically

AC C

EP

TE D

Possible influence of Ekg on energy consumption rate being analyzed