6.1 Impacts on EV sales shares
6.1.1 BEV sales share
Figure 3 shows the evolution in BEV sales shares between 2015 and 2050 under different scenarios. For BEV, all variables would appear to mainly act in an expected way up to 2030 under both Base and Mid Targets. There is little difference in magnitude or market penetration rates between Base and Mid until shortly before new targets are imposed in 2025. A small exception to this is reduced learning under the Mid target, which has led to marginally higher shares than either the baseline or maximum learning rate scenario by 2030. This occurs because from around 2025 the minimised learning rate exhibits a more rapid rate of sales growth than other scenarios. By this time the BEV has become relatively mature, so learning rates are more beneficial for the less mature FCV – making it more competitive – thus a lower learning rate is relatively beneficial for the BEV. Another anomaly is a higher sales growth rate (compared to baseline) when marketing is stronger at the start of the simulation, and a lower growth towards the end. This indicates that strong marketing when the BEV is first introduced is an important variable, but this boost is shifted to FCV when it becomes available (see section 6.1.3). Interestingly, the Base All Max scenario begins to be more successful than the Mid All Max scenario towards the end of this time frame.
In the period 2030–2050, greater differences due to fleet emission targets are more visible than in the initial 2015–2030 period. Perhaps most strikingly, the scenario with no targets and all variables at maximum have an increased market share of BEV compared to the same scenario with targets in place. This remains the most successful scenario (in terms of BEV sales share). This finding alone would suggest that when conditions are favourable towards BEV, fleet emission targets are unimportant. The same observation holds (to a lesser extent) for the marketing and GDP variables. Other anomalies witnessed are that reduced R&D and Learning effect are more beneficial for BEV than the maximised counterparts or baseline scenarios for the period from 2030. This is also true to a much more marginal extent from the about 2045 for marketing. These three manufacturer strategies, when maximised, are therefore more supportive of FCV than BEV. Under Mid Targets, there is a rapid sales growth around 2030, which increases even more after 2045. By 2050, the sales are at around the same amount as the baseline scenario. This again coincides with the introduction of FCV, suggesting that BEV benefits under conditions or strategies that are otherwise unfavourable towards e-mobility as they affect FCV more.
6.1.2 PHEV sales share
Up to 2030, PHEV exhibits similar, though more successful, market penetration to BEV. This can be be seen by comparing Fig. 4, which depicts PHEV sales shares, with Fig. 3. One reason for this is that there are two distinct PHEV models available (Petrol and Diesel) whereas only one exists for BEV. However, there are some key differences. The marketing variable does not have as large as an impact on PHEV early in the scenario as it does on BEV, though is the most influential variable by 2030 under either Base or Mid targets. The scenario where the GDP has the lowest growth rate leads to higher sales share than its maximised counterpart or the baseline scenario. This may indicate that under lower economic growth, users are less able to purchase the more expensive BEV. In the early days of an EV market, the PHEV, which is generally the most accessible EV for many users (with its lower price, closer characteristics to conventional vehicles and less reliance on charging infrastructure), may actually relatively benefit from our assumed e-mobility unfavourable conditions.
Up to 2050, there are greater differences between Base and Mid Targets for PHEV than for BEV, suggesting PHEV success is more sensitive to targets being in place than BEV. However, leading from the observations up to 2030 and similar to BEV, the All Minimised scenario continues to lead to a high sales rate and by 2050 is as successful as the All Max scenario. Thus, conditions and strategies that are unfavourable towards e-mobility push sales towards PHEV.
6.1.3 FCV sales share
FCV sales shares are shown in Fig. 5. By 2030, the highest FCV market share achieved under any scenario but the All Max is less than 3%, and the baseline scenario under Mid targets does not reach 1.5%. Under Base targets only the Maximised R&D scenario has achieved more than a 1% sales share. This is because these variables are more beneficial for PiEV during this period. R&D has the greatest influence on market uptake of FCV. This is in contrast to PiEV and indicates that R&D funding may go preferentially to FCV. Marketing starts to make a rapid impact towards the end of the time period, as it shifts preferences towards FCV.
Looking at Base conditions between 2030 and 2050, there is what could be considered as a failure to penetrate the market under all scenarios. Indeed from 2030 there is no growth in FCV sales share under any scenario without Mid Targets. Thus we can deduce that, in the confines of this model and our scenarios, manufacturer strategies will not support FCV without long-term, ambitious emission fleet targets in place. There is a very different story regarding mid-term targets however. The baseline scenario has a rather rapid sales growth between 2025 and 2045, which increases further from 2045 when new targets are visible to manufacturer. Marketing and R&D funding exhibit similar and expected patterns of market penetration though marketing was most influential by the end of the time period. Learning rates scenarios display similar market uptake to the baseline scenario but in the opposite way as expected (lower learning increases share and higher learning decreases share). The 2030 trend continues because this variable supports the earlier maturing PiEV over the lagging FCV technology. Indeed, lower learning rates have led to one of the most successful FCV sales shares by 2050. Furthermore, lower GDP and Oil price begin to produce greater FCV success around this time. The slowing in sales is due to the fact that from 2035 the current targets are being met, and no new tighter targets are visible to the manufacturer – therefore there is no additional incentivisation for FCV development or marketing that exists under the other variables. These findings suggest that manufacturer strategies are important for FCV success. This supposition is further supported by the large bandwidths between Max and Min scenarios for the manufacturer strategy variables. When all variables are set to their minimum values FCV experiences moderate sales growth from about 2035, leading to a 2050 share of around 10% of the market. When all variables are set to maximum values however, the market stagnates around 2035 and there is little sales growth until 2045 when there is a push in FCV by the manufacturer in anticipation of the 2050 target. Therefore, even with targets in place, certain market conditions and manufacturing strategies are needed to support FCV development.
6.2 Testing for the absence of FCVs
Although it is not realistic to exclude BEV or PHEV from our simulations, because they are already on the road, as we have identified certain interactions between powertrains it seemed an interesting venture to run some selected simulations without FCV. The impact of excluding FCV on EV market shares under various conditions is presented in Fig. 6. This meant for BEV and PHEV marginally higher sales under Base with maximum conditions. However less than 0.5% of share was added to either BEV or PHEV, as this “extra” share was split between all available powertrains. Under Mid targets both PiEVs attained higher shares (up to around 10%) under every scenario from just after 2025, when FCV would have made an appearance. However, more interesting than that is to look at the overall EV shares when FCV is excluded. Here we see that without FCV, under baseline scenario and maximum strategies total EV sales are the same. As the PiEVs do not have to compete against FCV for marketing, R&D funds or learning, they mature more quickly. Also, as they do not directly compete with FCV for sales, growth is more rapid.
6.3 Testing for subsidy regimes
Introducing the subsidies of Table 3 (in addition to those of the S1 baseline scenario), as in Fig. 7, has mixed impacts on total EV share under the varying conditions. Under base emission targets and variables, the purchase subsidies S2–3 marginally improve sales. When infrastructure subsidies are introduced (S4) in addition to purchase subsidies, this actually results in lower sales than purchase subsidies alone. This is because the infrastructure subsidies benefit BEV more than PHEV, so more BEV sales are occurring, thus reducing the development of PHEV and therefore the overall EV sales. When all variables are at their reduced value, the impact of infrastructure subsidies can be seen as it further reduces sales share from baseline. Purchase subsidies can marginally increase sales, but only after 2040. Finally, when the values of the variables are doubled, although the strongest subsidy scenarios results in the strongest EV sales, it is noted that the actual increase in sales from subsidies in any scenario is only marginal and may not be cost effective. Under Mid-Targets, subsidies make even less impact than under base conditions. This can be seen in Fig. 8.
The EV trends discussed above generally reflect the market pentration of BEV and PHEV. As discussed in previous sections, the FCV market fails under the Base emission targets. With purchase subsidies in place, sales can be encouraged between 2025 and 2035, but then the market stagnates. Infrastructure subsidies alone (S4) can lead to the best sales outlook, with a rapid increase from 2035. However, this still only leads to a 1% sales share by 2050. Nonetheless this shows the importance of infrastructure support for FCV under poor conditions. Under Mid emission targets, FCV is less sensitive to subsidies. Purchase subsidies barely increase sales, even when the values of the variables are doubled, and infrastructure subsidies lead to less sales. This is likely due to the subsidies being more beneficial for the PiEVs.