How fast is too fast for high-speed rail?

2 minutes

The right speed for a high-speed rail line comes down to trade-offs among many important factors. So how do regulators, investors, developers and other stakeholders ultimately decide what the optimal speed should be?

It has been more than 16 years since the French National Railway Company (SNCF) set the top speed record for a conventional train on steel wheels: 357mph (574kph).

Why is it then that today’s fastest high-speed rail services only reach top speeds of around 217mph (350kph)?

There are many reasons — including technical, economic, social and environmental considerations — and the optimal speed on one route may not be ideal for another.

Record speeds vs. realistic speeds

It should be noted that SNCF used a significantly modified TGV train to achieve that record speed in 2007. All unnecessary weight was removed, including all passenger and catering facilities. Heavy steel components were replaced with lighter composite materials. There were upgrades to the aerodynamics, power, traction and braking systems.

 The track itself was also perfectly straightened and smoothed —­­ the smallest kinks were removed, welds were ground flat, the smallest debris swept away. Increased power demands meant that the overhead catenary system had to be upgraded, and the train control systems were modified to manage speeds far beyond the normal limit of 186mph (300 kph).

 Given the extent of these modifications, it is easy to understand why speeds approaching 357mph (574kph) might not be realistic for an everyday passenger service. But why not 230mph (370kph), or 250mph (402kph), or 300mph (483kph)?

Over 16 years have passed since SNCF’s record run — 2007 was the year Twitter was founded and the first iPhone was launched — but we have only seen modest, incremental increases of the rapidity of high-speed rail services.

Optimization through simulation

The right speed for a high-speed rail line comes down to trade-offs among many important factors. So how do regulators, investors, developers and other stakeholders ultimately decide what the optimal speed should be?

One of the ways we do this is through detailed simulations that explore the trade-offs that can influence the optimal speed. As with many optimizations, the better the data, the better the results, and today we have vast datasets and the computing power to make use of them

Simulation example 1: Short trips and long legs

There is not point designing infrastructure for speeds that will never be reached in practice, such as when a proposed line includes many stations with short legs between them. With fewer stops, further apart, higher speeds make more sense.

Adding more stations can increase the socio-economic benefits of a high-speed rail line, and so there will be times when authorities or communities call for extra stops. We need to be able to quantify the impact of these decisions, answering specific questions, such as: How would the addition of another stop impact the total journey time? How would this change the optimal top speed of the line?

Let’s look at how our simulation can help with this, using a simple, theoretical scenario: a 311 mile (500 kilometer) straight and flat high-speed rail track with two stations, one after 93 miles (150 kilometers), and one after 171 miles (275 kilometers).

As we increase the speed of the line, naturally journey times come down, but the distance required to reach top speed goes up. Neither of these relationships are linear. As you can see in this chart below, for every 12mph (20kph) faster we go, we gain ever-smaller time-savings, while the distance needed to reach top speed gets bigger for every increment.

HSR speed vs distance and time travel

As with many other factors that influence the optimum speed, we get diminishing returns and higher costs, the faster we go.

(The simulation is of a double set high-speed rail train, capable of up to 249mph (400kph), powered by a 25kV AC catenary system. It assumes a dwell time of 180 seconds at each station.) 

 

 

In the 224mph (360kph) scenario, we only reach our target speed for a short distance between the second and third station. When the speed increases to 249mph (400kph) the line fails to reach its top speed for this leg of the journey.

We can use this to help us determine the impact of an additional stop. This chart represents our original scenario with two stops and a top speed of 224mph (360kph).

Let’s imagine the local government has requested a third station at the 233-mile (375-kilometer) mark, while central government has asked if the speed can be increased. This chart shows how the additional stop and increased speeds would impact the proposed line.

 

 

Percentage of total distance at top speed (2 stops)

  • 124mph (200kph) 96%
  • 162mph (260kph) 92%
  • 186mph (300kph) 88%
  • 224mph (360kph) 78%
  • 249mph (400kph) 65%

We can also see how, for all the legs, the distance required to reach top speed increases sharply after 224mph (360kph). It is more efficient, but often not possible, for a high-speed train to reach its top speed for a large part of the distance between every station. What is more important for the decision on optimal speed is the percentage of the total distance that can exploit the train’s top speed. In our simulation, this percentage falls from 78% (2 stops) to 70% (3 stops) at 360km/h.

Recall too that, for simplicity, the simulation assumes a straight, flat track, where top speed can be achieved and maintained without the changing elevations and curves which curtail speeds in the real world.

In terms of the total journey time, at 224mph (360kph), the addition of the third station adds 6 minutes and 49 seconds. If we increase the speed to 249mph (400kph), the third station would add 7 minutes and 35 seconds.

It is also important to highlight that the addition of a new station also results in an increase in energy consumption of 2.45 GJ, at a target speed of 224mph (360kph). If the line was powered by fossil fuel generated electricity, the additional station would therefore also increase carbon emissions.

 

Speed

[mph/kph]

Travel Time

Two stops

[hh:mm:ss]

Travel Time

Three stops

[hh:mm:ss]

Travel Time increase

[hh:mm:ss]

Energy increase

[GJ]

124 / 200

02:41:16

2:46:03

0:04:47

0.99

137 / 220

02:28:15

2:33:13

0:04:58

1.18

149 / 240

02:17:32

2:22:43

0:05:11

1.37

162 / 260

02:08:37

2:14:02

0:05:25

1.57

174 / 280

02:01:07

2:06:46

0:05:39

1.78

186 / 300

01:54:45

2:00:40

0:05:55

1.97

199 / 320

01:49:20

1:55:32

0:06:12

2.15

211 / 340

01:44:44

1:51:14

0:06:30

2.29

224 / 360

01:40:49

1:47:38

0:06:49

2.45

236 / 380

01:37:31

1:44:42

0:07:11

2.60

249 / 400

01:34:47

1:42:22

0:07:35

2.30
HSR speed vs distance.


Simulation example 2: Megawatts for mega-speeds

Is it worth it? This is the big question behind faster high-speed rail, and it concerns both natural and financial resources. Let’s look first at energy and power, setting aside economic costs for a moment. 

High-speed rail developers need to consider how they will secure reliable supply of sufficient electricity. Higher speeds require more power. The existing grid may not be able to cope, which could necessitate lengthy and costly development of the surrounding power grid infrastructure.

As with time and distance, the relationships between speed and energy, and speed and power, are non-linear. In other words, as we get faster, every additional mile-an-hour of speed, costs more energy, and demands more power, than the last. 

 

 
HSR speed vs maximum demand power and total energy

But as energy consumption and power demanded rise significantly, we make ever smaller savings on our total journey time. For instance:

  • To go from 149mph (240kph) to 162mph (260kph) requires 64GJ of additional energy and 0.85MW more power. Which is equivalent to the average daily electricity used by 100 households (considering an average daily use of 10 kWh). If we have trains every hour and in both directions (15 per day and direction), the energy needed for this speed increase is equivalent to that of 3000 households. This change would reduce the total journey time by 8 minutes and 55 seconds
  • But to go from 211mph (340kph) to 224mph (360kph) requires 18GJ of additional energy and 1.56MW more power. Which is equivalent to the average daily electricity used by 145 households. If we again have trains every hour in both directions (15 per day and direction), the energy needed for this speed increase is equivalent to that of 4,350 households. But this change would only reduce the total journey time 3 minutes and 55 seconds.

 
HSR speed vs time travel vs power
Increase in total energy and power demand respect to a 200km/h baseline

The variety of variables


The number of stations, energy consumption and journey times are just a few of many factors that must be considered before arriving at an optimal speed. These include both high- level and technical issues, for example:

  • Finance: Higher speeds increase railway infrastructure costs and operational costs. There is a point at which costs become so high, and incremental gains so small, that it becomes more beneficial to move away from the steel wheel and tracks of traditional high-speed rail and explore the potential of maglev or hyperloop technologies. 

  • Sustainability: Faster speeds drive up the carbon emissions for high-speed rail lines that rely on fossil fuel power generation. But even when a high-speed rail line is powered by renewable energy, we need to consider overall resource efficiency and responsibility. Excessive use of clean energy to make small gains in journey times might be unsupportable when that energy could instead be used to displace high-carbon energy from another sector. 

  • Impact: High-speed rail lines must make a major positive impact to justify the time, effort and expense of their development. The speed of the line needs to support a service that comfortably out-competes alternatives, makes a transformative difference, and results in a large and broad enough socio-economic uplift to justify the investment.

  • Safety: As trains go faster, the risk of derailment and other accidents increases. This means that systems and operating procedures become more stringent.

  • Power: Transmissions lines will need to be refurbished or replaced to deliver enough power. Larger, and more frequent, traction substations will be needed, along with more complex and robust power delivery systems.  

  • Curves: Safety and comfort constraints limit the speed at which trains can take curves. For a speed of 224mph (360kph) the required curve radius is about 6.2 miles (10 kilometers). For 249mph (400kph), this increases to 7 miles (12km). 

  • Geography: Valleys, mountains, rivers and other natural features can make it difficult to avoid changes in direction and elevation, reducing the potential for high speed, or adding to costs if tunnels, bridges or viaducts are needed to make the route straighter and flatter. 

  • Prohibitions and obstructions: Existing infrastructure, buildings, national parks, sacred ground, and other factors impact routes in the same way as geographical features.

  • Tracks: Higher speeds need specialized materials, tight manufacturing tolerances, continuous inspection and more frequent maintenance. 

  • Trains: Going faster means lighter, more aerodynamically efficient trains with powerful motors and braking systems. 

  • Noise: high-speed trains are loud, especially at extreme speeds. This can be a major concern for communities located near high-speed rail lines.

  • New phenomena: Significantly higher speeds could introduce new challenges, costs and technical limitations. For example, trains could begin to lift and disrupt ballast from beneath the train in new ways. This may not only damage the train and the tracks, but also harm people, property and the natural environment. 

    Addressing all these factors in the pursuit of faster high-speed rail adds to costs, risks and complexity — with many avenues leading to sharply diminishing returns as speeds increase. At present, it seems that few new or existing high-speed rail corridors could justify speeds of more than 217mph (350kph), all things considered. 

    To arrive at an optimal speed, decision-makers must balance these many variables without making unacceptable trade-offs. This will always be a difficult challenge, but at least today we can use the data and simulations we have to make this considerably more precise and predictable than in the past. 

Methodology

The simulations in this article were conducted with software called RailEST (Railway Electrification Software Tool) which was designed and developed by AECOM in Madrid, Spain. RailEST was planned as a versatile tool from its inception, a tool that could provide solutions using different standards and for different clients and scenarios. This versatility makes RailEST more than a specific calculation application, it is a tool in continuous evolution and improvement that can integrate different calculation modules and capacities, giving added value to our projects. AECOM uses the tool in engineering and consultancy services to deliver efficiencies and insights throughout the design process, from inception to commissioning.

 

From vision to reality

For more detailed analysis on high-speed rail insights and best practices, read our high-speed rail playbook
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