Bike upgrades - Which offer the best value for money?

I did this analysis in 2016.  In fact, it was the first significant piece of bicycle performance analysis that I did, or at least, it’s the first study that's worth writing about.  The objective was to calculate which road bike upgrades offered the best value for money, in terms of making me faster on the bike.

I have been a keen cyclist for years, since about 1994 when I bought my first bike, a cheap £200 mountain bike.  In those first 15-20 years of recreational cycling, I frequently upgraded my bike(s) with new and better components. Like many other people during that era, I focussed on making my bikes lighter.  I was a bit of a weight weenie in those days, I'm ashamed to say.  Sadly, I can’t even say that my fitness justified the attention to detail that I put into my bike upgrades.

In the winter of 2015/2016, I realized that I knew everything necessary to model the forces and power losses that occur when riding a bike, and I was therefore able to analyse and quantify how much benefit could be achieved by making various improvements to either the bike, the kit or it's rider.  Doing so would mean that I had the possibility to check how beneficial all those weight savings had been on my cycling performance and how beneficial other types of improvement would be.  In turns out that I was in for a bit of a shock...

Method

My previous blog post explains the Excel-based method I created to model the power required to propel a bicycle at a certain speed and for certain set of conditions. That performance model development was a precursor to the analysis described in this post.  The Excel-based performance model also allows the power delivery/speed profile to be optimised for a prescribed cycle route (i.e. a gradient profile).  This optimisation functionality is important, because changes in bike equipment might lead to a slightly different optimised power profile that achieves the fastest bike speed (or in terms of how the actual computation is done, a slightly different optimised speed profile that achieves the prescribed average/normalised power constraint).

Re-optimisation example

The example below illustrates this, for a case where 2 kg is removed from the bike weight.

Case 1 in the table below is the optimised power profile for a 80km route described in the previous blog post, with the speed profile optimised to maximise the average speed (i.e. minimise ride time) for a prescribed normalised power of 200W.  In case 2, the weight is reduced by 2 kg, but the same speed profile is maintained. This results in a reduced normalised power of 197.294W, so a saving of about 3W (i.e. 2kg weight saving gives a 3W saving at the same speed).  For case 3, the same 197.294W normalised power is used as a constraint, and the speed/power profile is re-optimised.  This gives a small 3.6 second time improvement.

Although this re-optimisation change is very small, I wanted to do the power profile re-optimisation for each bike modification analysed to provide the best like-for-like comparison.  I also couldn't be sure that some bike modifications wouldn't affect more significantly the optimised power/speed profile.  I also think it's more relevant to know the speed improvement associated with a modification, for a fixed power, rather than a power improvement, since we tend to ride at a given power target/limit (our maximum capability) instead of targeting speed. The speed improvement is only achieved in my Excel model by re-running the optimisation.

                                     Bike weight        Avg Power       Normalised Power       Time           NP improvement

1) Optimised Power                 7 kg                192.6 W                 200.0 W         2 hrs 51.11 mins                -

2) Same speed profile as 1     5 kg                191.7 W                 197.3 W         2 hrs 51.11 mins             -2.7 W

3) Optimised speed profile     5 kg                191.7 W                 197.3 W         2 hrs 51.05 mins             -2.7 W

Bike modifications analysed

For the modifications I analysed, I considered a range of changes to the bike that would affect one of the forces of resistance acting on a bicycle:

• Aerodynamic resistance - Expressed via the CdA value (drag coefficient multiplied by frontal area) in the model. Items like aerodynamic helmets, deep section wheels, skinsuits etc.
• Rolling resistance - Expressed via the CRR (rolling resistance coefficient) value. Items like cheap versus expensive tyres, mountain bike tyres versus road tyres, inner tubes etc.
• Weight effects - Generally only affect the bike performance when riding uphill, but there is also a very small effect on rolling resistance on the flat too. 

In addition, I also looked at power changes, which would come from fitness improvements.  Again, the objective of all this was to understand relative differences between these changes.

Data sources

At this point, it's worth mentioning where I got my data from:

• For aerodynamic changes, I reverse-engineered the 40km time savings quoted by Specialized in their Wind Tunnel YouTube series.  I did this by iteratively determining the CdA reductions in my model needed to achieve the 40km time savings that the guys at Specialized quote.
• For rolling resistance changes, I took data from bicyclerollingresistance.com.
• For weight changes, although most changes were arbitrary changes like 1kg or 5kg reductions, I equated this to tangible changes like the cost of buying a more expensive groupset by looking at price data on Wiggle and weight data from bike component manufacturers such as Shimano.  For example, a Ultegra grouset will cost around £400-500 more than a 105 groupset, but will save around 200-300g.

Routes considered for analysis

I considered the same three fictional routes that I described in my previous post. Most of the items were analysed for Route 1, which is typical of many medium length sportives that might be done in the UK.  Results for routes 2 and 3 give some indication how sensitive the results are to the amount of climbing, which can be interesting because, for example, the effects of weight reductions on flat routes are almost negligible.

Route 1: Typical short/medium sportive - 80km route, 1000m of climbing, 200W normalised power.

Route 2: 40km TT - 40km perfectly flat route, 250W normalised power.

Route 3: Hilly route: 40km route with 900m of climbing, 250W normalised power

Baselines values

The various modifications analysed were considered relative to the following set of reference conditions:

• Air pressure = 1012.5 mbar (i.e. International Atmosphere sea level pressure)
• Air temperature = 20 degrees C
• Air density = 1.203 kg/m3 (calculated from the above pressure and temperature)
• Bike weight = 7kg
• Rider Weight = 11st 7lbs (161 lbs or 73.2kg)
• CRR = 0.045
• CdA = 0.36 m^2

Results

The table below shows the results for a number of bike modifications, with percentage time improvements ("% change" column) calculated either relative to the baseline setup above, or versus a degraded setup.

The cost effectiveness column called "cost per 1%" shows which modifications offer the best ride time improvement (or average speed improvement) for the money.  Green and yellow boxes show the best value for money modifications, whereas red items are poor value for money.

Improvements and cost effectiveness of various bike modifications

 There are a few key takeaways from this study:

• Power improvements: If you can improve your power, through improved training etc, at no extra cost then that is a very effective way to improve your average speed. For the 80km route, a 5% power improvement gives a 2.57% speed improvement.

• Optimised power: As discussed in my previous blog post, even if you are not any fitter, applying more or less power at the right time (i.e. optimising your power delivery) gives a significant 2.02% average speed improvement versus a constant power approach, even though the normalised power is no different.

• Rolling resistance improvements: By far, the best value for money upgrade you can make to a bike is improvements to your tyres and tubes.  Upgrading tyres and tubes will typically provide a cost effectiveness in the region of £30 per 1% improvement.  Even if you start from good tyres, like Conti GP 4000s tyres, upgrading to the best tyres is still less than £100 per 1% improvement.

• Weight: On the other hand, buying expensive components that will make your bike lighter are extremely poor value for money.  I have used the assumption of £1 per gram saved, which is a typical price you'll pay when going for a next tier groupset for example such as buying Dura Ace instead of Ultegra.  Spending £1000 to save 1kg will improve you average speed by only 0.38%, so that's around £2000-£3000 per 1% improvement!

• Aerodynamic improvements: The value for money of aero improvements is in the middle, with aero wheels and aero frames being quite costly, per 1% improvement, but aero helmets being a more cost effect upgrade.  Getting a tighter fitting jersey is a very cost effective improvement, rivalling the tyre and tube upgrades in terms of bang for your buck.

The numbers in the table above are a little difficult to read, admittedly, so I pulled a few of them into the chart to show visually how certain improvements are significantly better than others, in terms of value for money:

From this chart, it's clear that buying upgrades to improve rolling resistance is money well spent.  The aero improvements shown all give broadly similar average speed improvements in absolute terms, as said in the Specialized video with their time-saving-over-40km metric.  However, buying a tighter fitting jersey will be about one tenth the price of aero wheels or a new bike frame, so clearly a tight fitting jersey represents much better value for money.

As for weight improvements?  Well, since the bars on the right hand side of the bar chart are barely visible, spending money to make your bike lighter is extremely poor value for money, when it comes to actually going faster.  It seems that all the money I spent on lightweight components for many years was, sadly, a unwise choice.

Trades

It's finally worth showing some 'trades', i.e. what changes are equivalent, in terms of the resulting bike speed improvement.  These values have been obtained from the results above and their associated changes to either power, weight, drag or rolling resistance.

A 1% speed increase is achieved by:

Either a...   1.95% power increase

     Or a...    0.00077 CRR reduction

     Or a...    0.0153 m^2 CdA reduction (=4.3% CdA reduction)

     Or a...    2.67 kg weight reduction

 

Conclusion

In summary, spend your money on fast tyres and tubes as a priority, then upgrade to a tight fitting jersey.  For around £150, buying fast tyres, latex tubes and a tight jersey could improve your speed by 4-5%, depending on your starting point.  On the other hand £150 spent on lightweight components won't even improve your speed by 0.1%!

Finally, improving your power output, either by getting fitter to raise your power, or by optimising your power delivery, is a very effective way of going faster on the bike.