How tough is it going to be for automotive OEMs to hit carbon dioxide (CO2) targets? The answer is, not surprisingly, "it depends." But what that dependency actually is might surprise you. We think that how effectively OEMs achieve the targets is directly related to how fast they accelerate changes in the way they adopt technology and adapt their processes to maximize its use in development programs. Make no mistake. The CO2 challenge is massive. Consider the nearby graphic copied from the UK-based Society of Motor Manufacturers and Traders' (SMMT) "New Car CO2 Report 2014". It shows that EU 2020 targets mandate an additional 26% decline in CO2 output measured in grams per kilometer from the 2013 targets. In the US, the targets are even tougher: the combined fleet must reduce CO2 output in 2025 by 35% from 2016 levels. Imagine it: double-digit CO2 reductions delivered on tight timeframes in products that cost billions to develop. It's enough to make auto executives sleepless. So, why, you might ask, are we suggesting that achieving these targets may be easier than many OEMs think? It's because more widespread use of aerodynamic and thermal simulation during the design and engineering processes can get the industry there. Yes, it's a process change for some OEMs. And, yes, that may mean that some old ways of thinking (like running to the wind tunnel after every change) need to give way to digital iterations of design changes. But for those OEMs who are already far along in their efforts to change the way the way they design new cars, these targets just don't seem so daunting. Consider what Wolfgang Ziebart, head of Jaguar Land Rover's product development, recently told Automotive News Europe (subscription required) when asked how hard it would be for JLR to reach CO2 targets:
We don't need completely new inventions. The technology to meet the targets is available. For 2020, it will be very much about selecting which technical solutions are appropriate so that the targets are met, but at a cost that's within certain limits.
This doesn't sound like someone who's losing sleep about these targets, does it? Want to know more about what JLR knows? Just ask us.