Originally posted by Big Bird:
Lap simulation, linked to pointscoring analysis. Can't go past it. You'll learn heaps.
A perfect lapsim will take a year. A simple lapsim will take a day, if that. The perfect lapsim is a refinement tool, for when you are tuning your established concept around a known track. The simple lapsim will give enough info to form your concept, which is what you want at this stage.
Try to answer the following questions:
A 1kg or 1 lb difference in vehicle weight is worth ... points.
A 1hp or 1kW difference in power is worth ... points.
A 1% increase in braking deceleration is worth ... points.
A 1% increase in forward acceleration is worth ... points.
A 1% increase in lateral acceleration is worth ... points.
From the above, come up with rules of thumb like "A 1% increase in cornering acceleration returns ... times as many points as a 1% increase in braking decel".
Your answers don't need to be exact, just good enough to guide your overall understanding of the comp.
With the above, you can then make top level decisions between concepts on a "points per time required" and "points per dollar" basis.
By simple lapsim, think the following: track = straight lines and arcs, lateral grip limit determines corner speed, and start with constant accel and decel. Any track will do. Once you have that working, try to implement power-driven acceleration. Then include aero drag and rolling res if you like. An energy analysis can drive fuel economy comparisons between concepts. Grip limited vs. power limited accel is easy with a bit of thought. All of this can be done simply in Excel.
Remember that the engine has a number of attributes that affect the overall vehicle - weight, power, packaging, economy. Choosing an engine based on straight line accel (for example, selecting only on the "power:weight" criteria) doesn't account for how the engine affects other parts of the track (i.e. when power attribute is "off", but weight, economy & packaging attributes are still definitely "on").
As a team, spend a week performing and assessing the above. Get everyone to the same level of understanding. Choose the most appropriate solution for your resources, put a freeze on it and move on. Either engine choice can be competitive, but your understanding and team cohesion will be hugely enriched by working through the process.
Decision matrices are great when they are populated with quality, (read, quantified and justified) data. But as said above, more often than not they are just formalized guesswork. Most I've seen have been awful and are only used to justify a pre-determined solution.
Cheers,