Comprehensive effects of policy mixes on the diffusion of heavy-duty hydrogen fuel cell electric trucks in China considering technology learning

Abstract

Heavy-duty hydrogen fuel cell electric trucks (HD-FCETs) will play a pivotal role in achieving carbon neutrality in transportation in China. However, high cost has hindered its commercial diffusion, resulting in the dependence on financial policy support. With the phasing out of purchase subsidies, new policy mixes should be proposed. Therefore, a modified generalized Bass model based on technology learning is established to investigate the comprehensive effects of various policy mixes on the HD-FCETs diffusion including tractor-trailers, dump trucks, and straight trucks. About 113 policy mix scenarios - consisting of one or more policy tools from sales ban policy, hydrogen subsidy, and purchase tax - are simulated. The obtained results reveal that: (i) All policy mix scenarios can increase the ownership amount of HD-FCETs by 1.92%–35.7% by 2060 compared with no policy scenario; (ii) The most efficient policy mix scenario can reduce the cumulative social costs from 323.69 billion CNY to 210.3 billion CNY, while inappropriate policies and no technological advances could increase the cumulative social costs to 356.6 billion CNY and 732.6 billion CNY respectively; (iii) Among these policy tools, the sale ban policy is indispensable, moreover, both the HD-FCET classes and the policy intensity can affect the optimal policy mix choice.