photo AUIQ_memberbanner_35k_zpshpuehyuc.png

You are here

The challenges of experimental engines and optimisation

Contributor: Chris Brace
Posted: 01/11/2015
Rate this: 
Be the first!

Automotive IQ recently spoke with Chris Brace, Professor at the University of Bath, about his Chassis Dynamometer research, the main drivers for engine optimization and how less aggressivity might lead to significant fuel savings.

Prof. Brace, could you please tell us a bit about your work in general and your current projects regarding engine optimization?

I’m Professor of Automotive Propulsion and Deputy Director of the Powertrain Vehicle Research Centre at the University of Bath, working on powertrain and engine systems. We have projects across the powertrain application area. Probably the highest profile project we have in the moment is based on research funding by the EPSRC (Engineering and Physical Sciences Research Council) in the UK which is funding a refurbishment of our Chassis Dynamometer.

What are the capabilities of the Chassis Dynamometer?

We established the Chassis Dynamometer 13 years ago and it has done good work for us over the last decade in vehicle and powertrain research. The new funding will us allow to increase the capability a lot, it will be a four wheel drive machine. It will have significantly more emission measurements equipment, much more environmental capability, a state of the art robot driver, electric vehicle capability and also improvements to the precision of measurement. The reason for doing all this is to address the real driving emissions requirements that will be going into the emissions legislation and already are shaping what the automotive OEMs and Tier Ones need to do in terms of R&D. The traditional approach of moving from simulation through to engine dynamometers through to vehicle needs to be challenged and much more attention paid to the in-vehicle optimization.

If you look at your recent projects where do you see the greatest benefits in engine optimization?

The most high profile engine research project we have worked on has been the Ultraboost Project which was led by Jaguar Land Rover and co-funded by the TSB (Technology Strategy Board) which allocates UK Government funding to collaborative R&D projects. The project was designed to produce a downsized gasoline engine that would replace the 5 Liter Jaguar Land Rover with a 2 Liter Turbo Super engine that produced the same torque across the engine speed range as the 5 Liter NA engine. So, that meant downsizing by a factor of 60%.

What is the main motivation behind downsizing and engine calibration is it primarily about fuel economy and CO2 emission reduction?

Yes, the motivation here was to reduce CO2 emissions, relative to the baseline 2012 Range Rover, by 35%. And we achieved this, not only through the engine, there were other improvements that were made possible by the engine downsizing. It's an experimental engine, not intended for production. But there is knowledge that comes from that research program that will definitely influence future engine production.

What are the main challenges with experimental engines and optimization?

When you have engines of this type, that are very highly downsized, very complex systems, you firstly have a challenging calibration task and secondly, if you are moving into an environment where real driving emissions are more heavily scrutinized than ever before, that itself makes calibration task hugely more complex because you are looking at a much wider range of operation in much more detail than the industry has been doing until now.

There are very large areas of interest that can’t be addressed on a standard engine dynamometer. You need to have dynamic capability across the full engine envelope but you also start to need climatic capability and environmental control and you also need the interactions with the other parts of the vehicle system and all the components need to be represented in some way in the calibration study. The traditional vehicle calibration program relies on having most of the hard work done early on using the engine platform. This will be more challenging in the future.

How does the commercial side of the research collaborators play out on the constant attempt to reduce costs in the production cycle?

If you’ve got a given cost structure that you need to be aiming at, that will strongly influence your hardware choices. As you get closer to production you reduce your options and select components that you know you can achieve in a commercial setting. Then the challenge for us in the University is to find techniques to optimize the performance attributes of the system within the constraints of the commercially viable system. We are directly affected by component and specification choices that come from the commercial side of our collaborators’ business.

This approach can be improved upon in the future. Right from the early stages of powertrain design, you do need to have a simulation environment that can of course replicate the physics but also can encapsulate the costs and perhaps even the life cycle implications of the technology. As you rearrange and scale the hardware to achieve the performance attributes you want, the cost and life cycle attributes also need to be updated to reflect the changes you have made. We don’t yet have simulation tools that have all of those features. We’re getting there in terms of the physical attributes but there are still some areas we need to work on to improve the tools and techniques. For now, the flow is less integrated. Technology choices are set by strategists within the automotive companies and we optimize within those constraints.

You are also interested in human behavior when driving and the impact this can have on fuel economy. What has to change in the mindset of drivers to really make a difference in the future?

I think the mindset of drivers is changing in several ways already. If you look at the choices of vehicles that people are buying now there is a move towards acceptance of smaller engines, although not so much in terms of lower performance. People still like to have the performance attributes but there is more of a mood to compromise in favour of fuel efficiency. So this is influencing the initial purchasing behavior. Buyers are more willing to consider future ongoing costs as well as just the initial purchase price.

But what about the actual driving behavior?

That’s much more difficult because if you look at people’s rational intentions, they would say ‘sure, I need to drive economically because fuel is expensive'. Even if they don’t consider the wider environmental considerations, the financial implications lead them to believe that they should be driving economically. However, not everybody understands what this means in terms of driving behavior. So increased driver assistance to help us to drive economically is needed.

Part of that is around aggressivity. If you can measure the aggressivity of the drivers and find a way to reduce it, then you’re going to achieve significant fuel savings. We’ve been involved in the development of a commercial device sold by a small company in the UK, they manufacture a product which uses the On-Board Diagnostics (OBD) data to monitor aggression and to advise the driver when they are exceeding preset thresholds. The device reports back to the fleet manager, who is able to monitor the behavior of drivers and reward good behavior. This system has demonstrated significant effects, often in excess of a 12% fuel economy benefit across the fleet.

Thank you for your time.

Thank you, for your interest in, The challenges of experimental engines and optimisation.
Contributor: Chris Brace