 |
|
|
|
|
|
|
 |
General information
|
|
|
|
|
|
|
| |
|
|
|
Description
|
| |
|
|
|
|
A number of components of the power train of modern electric stock are
regulated and operated by an on-board computer. The corresponding software is
fixed by the manufacturer and usually not modified by the railway operator. In
many cases this software offers considerable potential for optimisation from an
energetic point of view. In this case a modification of existing stock in
co-operation with manufacturers is an interesting option.
The principle consists in changing the setpoints of inverter control
according to the value of other parameters such as catenary voltage, wheel-track
conditions or speed.
This includes optimising the setpoints of the following quantities:
• Voltage in DC link
• Magnetic flux in motor
• Pulse frequency of rectifier and traction inverter
• Pulse pattern in traction inverter
All the target values of these quantities have to be optimised at the same
time. The effect of such a measure on energy consumption may be illustrated for
the case of DC link voltage. Virtually all constant (as opposed to power
dependent) losses in the inverters depend quadratically on DC link voltage. The
reduction of this voltage during low load periods therefore cuts energy
consumption to a considerable extent. |
|
|
General criteria
|
|
|
|
|
|
|
| |
|
|
|
Status of development: in use |
| |
|
|
|
|
Theoretical optimisation of electric components has been studied and is well known. The required software change depends on individual vehicle series and manufacturer. |
|
|
|
|
| |
 |
|
|
Time horizon for broad application: in < 2 years |
| |
|
|
|
|
(no details available) |
|
|
|
|
| |
|
|
|
Expected technological development: basically exploited |
| |
|
|
|
|
The underlying optimisation algorithms are basically known. |
|
|
|
|
| |
|
|
|
Motivation:
|
| |
|
|
|
|
Energy efficiency |
|
|
|
|
| |
|
|
|
Benefits (other than environmental): none |
| |
|
|
|
|
(no details available) |
|
|
|
|
| |
|
|
|
Barriers: low |
| |
|
|
|
|
Human resources
Since propulsion software is not prepared for later modification and differs
between vehicles, the required changes can only be realised by or in
co-operation with the software engineers having programmed it in the first
place. Many times this turns out to be a barrier for two reasons: Usually,
software engineers who developed a particular solution are not always available.
A software engineer not familiar with the particular train software would need
too much time to understand the software in order to change it. Best chances of
finding the right person exist, if the particular vehicle series is still
produced. Since software engineers are a scarce human resource, many
manufacturers will be reluctant to put them on a task that is not considered
their core business.
IT-equipment
The computing capacity installed on older locomotives is sometimes not
sufficient to implement additional features. Since propulsion software is a
real-time application, any modification slowing down the system too much may
lead to dysfunctionalities in propulsion. |
|
|
|
|
| |
|
|
|
Success factors:
|
| |
|
|
|
|
When purchasing new stock, the degree of optimisation should be evaluated. |
|
|
|
|
| |
|
|
|
Applicability for railway segments: medium |
| |
|
|
|
Type of traction: electric - DC, electric - AC
|
| |
|
|
|
Type of transportation: passenger - main lines, passenger - high speed, passenger - regional lines, passenger - suburban lines, freight
|
| |
|
|
|
|
In principle, most locomotives and MUs of all power classes can be
optimised. However, it has to be examined for each vehicle series to what degree
the software is optimised already. For German DB the locomotive series BR 101,
BR 145 and BR 185 (still to be delivered) could be assessed for optimisation.
One hardware condition lies in the installed computing capacity which in
older stock may not be sufficient in order to allow for a modification (cf.
barriers). |
|
|
|
|
| |
|
|
|
Grade of diffusion into railway markets:
|
| |
|
|
|
Diffusion into relevant segment of fleet: 0 % |
| |
|
|
|
Share of newly purchased stock: 0 % |
| |
|
|
|
|
Only example known is Swiss Re 465. |
|
|
|
|
| |
|
|
|
Market potential (railways): medium |
| |
|
|
|
|
(no details available) |
|
|
|
|
| |
|
|
|
Example:
|
| |
|
|
|
|
Swiss Re 465. The optimisation measure was favoured by the fact that the locomotive series was still in production at the time, so the software experts were available. |
|
|
Environmental criteria
|
|
|
|
|
|
|
| |
|
|
|
Impacts on energy efficiency:
|
| |
|
|
|
Energy efficiency potential for single vehicle: 2 - 5% |
| |
|
|
|
Energy efficiency potential throughout fleet: < 1% |
| |
|
|
|
|
Experts calculate a theoretical saving potential of 15% achievable through traction software measures.
In practice, an ex post software improvement will typically raise energy efficiency by 1-3 % depending on vehicle and the degree of software optimisation already realised by the manufacturer. For large series (such as DB’s BR 101) even a small improvement potential of only 1% can economically justify such a measure. |
|
|
|
|
| |
|
|
|
Other environmental impacts: neutral |
| |
|
|
|
|
(no details available) |
|
|
Economic criteria
|
|
|
|
|
|
|
| |
|
|
|
Vehicle - fix costs: low |
| |
|
|
|
|
Mainly personnel costs for realising software change. Strongly dependent on number of identical vehicles. |
|
|
|
|
| |
|
|
|
Vehicle - running costs: significant reduction |
| |
|
|
|
|
(no details available) |
|
|
|
|
| |
|
|
|
Infrastructure - fix costs: none |
| |
|
|
|
|
(no details available) |
|
|
|
|
| |
|
|
|
Infrastructure - running costs: unchanged |
| |
|
|
|
|
(no details available) |
|
|
|
|
| |
|
|
|
Scale effects: medium |
| |
|
|
|
|
For every vehicle series personnel costs for realising software change are fix costs. There are therefore strong scale effects achievable when optimising a large vehicle series. |
|
|
|
|
| |
|
|
|
Amortisation: (no data) |
| |
|
|
|
|
Amortisation periods heavily depend on number of vehicles in one series and optimisation potential but will be generally short. |
|
 |
Application outside railway sector (this technology is railway specific)
|
|
|
Overall rating
|
|
|
|
|
|
|
| |
|
|
|
Overall potential: promising |
| |
|
|
|
Time horizon: short-term |
| |
|
|
|
|
A software optimisation of the power train of existing stock will in many cases offer appreciable potential for energy savings. The feasibility and profitability of such a measure is to be assessed individually by experts. Generally large series are the most interesting candidates. When purchasing new stock, the degree of optimisation should be evaluated. |
click icon to print 
date created: 2002-10-04
