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In 2018, about 45.42 million low-speed electric vehicles (LSEV) were produced in China, a 3.9% rise on an annualized basis (a 1.6-fold figure compared with China's output of 27.81 million automobiles in the year), but LSEV witnessed a slowdown in growth rate due to policy impact.
The LSEV market is largely dominated by electric bicycle and electric tricycle, both of which held a combined share of roughly 95% by output in 2018.
Low-speed electric vehicle (LSEV): In 2018, China issued a policy prohibiting new capacity of low-speed electric vehicles.
In competition, Yadea and Aima are the two key players in the electric bicycle market, together grabbing around 25% shares in 2018; the electric tricycle market is dominated by Kingbon and Zongshen; Levdeo as a bellwether in the LSEV market seized 21.4% shares in 2018, closely followed by YOGOMO 11.2% and Shifeng 7.5%; the ATV market is an oligopoly with Cfmoto Power and Linhai holding a combined over 80%.
In China, a surge in rural road mileage will favor the expansion of the LSEV market as such vehicles are hugely demanded in the third- and fourth-tier cities.
This study used five proxies (LSE, LSEG, HE, LSEV and EE) for human capital (HK) and regress on HDI as proxy of economic development with addition of log of capital formation (LK).
It is easy to verify that v is a LSEV associated with the eigenvalue [lambda] = 3 (see Example 2.16).
We adopt the terminology of functional analysis (where the support of a function means the subset of the function's domain where the function is nonzero) and call the eigenvectors that are nonzero only on a local substructure locally supported eigenvectors (LSEVs).
In Section 2, we define LSEVs and establish algebraic conditions that yield LSEVs.
The connection of considerable portions of these eigenspaces with LSEVs is verified.
In this work, we emphasize the computational importance of the sparsity of the LSEVs and demonstrate that these vectors can be used to efficiently reduce the original graph into a smaller graph that perfectly represents all other eigenvectors that have not been identified as LSEVs.
provides innovative integrated Lithium-ion battery systems deploying high-quality LiFePO4 cells to power low speed electric vehicles (LSEVs) and emerging applications.
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