Fuel & Service Data Analytics

Historically it has always been difficult to accurately measure any technology or additive that claims to improve fuel performance and reduce on-going maintenance costs.

The reason for this is that the customer, who has a specific test agenda set by their board of directors, generally carries out the testing. So what they measure often varies and therefore logically, so does the result.

In general they are all looking for types of improvement in general fuel performance, be it reduction in exhausted emissions or an increase in power output or an improvement in overall fuel economy.

There are 5 key factors that always skew the results:

The differences in engines tested – type, age, service interval and combustion state compared to baseline performance (new) all have a large effect.
The differences in fuel grade/quality - the condition and age of bunkered fuel used in testing often varies depending on each operator’s maintenance regime.
The difference in driver performance – the timing and selection of each gear ratio has a huge effect on both power and economy. Without instant feedback or training driver performance will always vary and not achieve best performance or economy.
The differences in load/tonnage – The load for each test run / period is critical because accelerating and decelerating a heavier mass reduces economy and uses more power. This reduces fuel performance and increases wear and tear on both engine, gearbox and brake parts.
The frequency of the stopping schedule – Directly related to point 4. The same train on the same route often has different route plans depending on time of day. At peak times, trains will collect from more stations. This increases income but also load. The frequency that you have to accelerate this increased load will have a direct effect on the fuel performance, economy and emissions of each run. This means, that even with the same driver on the same route, with the same train – results will vary.

In fact, the longer the period of testing, the more inaccurate the results become because the entire test becomes more and more variable. Which is ironic as most tests are carried out over a 6-month period or longer.

The good news is that even with all of the variables above not being measured or accounted for, 205 independent rail locomotive engine tests ALL showed improvements in engine power and fuel economy using our fuel catalyst - ferrous picrate (FPC).

Loco engines already tested and approved include EMD (General Motors), Caterpillar (who acquired EMD in 2010) and GE (General Electric). For a summary of these results please click here:

So the challenge for VFT was to find a way for the operator to access, acquire, analyse and feed all this data into a real-time filter engine to accurately measure the real results.

We did this by using three existing proven technologies we developed for rail and haulage by our sister company Vidiwave Limited.

The first step was to use and develop a new version of the CANBus data acquisition module DAAM for the rail sector.

This is an on-going programme of R&D that involves scanning loco engine feeds, VCU’s and CANbus interfaces to access and collect relevant data from the train’s internal data bus relating to fuel performance.
At the same time we scan and collect data relating to general service and maintenance of the vehicle. This enables operators to pre-plan service intervals and routine engine maintenance based on need – not routine

The second step was to find a secure method of transferring all the data off the train and into a cloud-based data server to do all the analytics.

Again this was achieved by re-using an existing VPN hardware / software platform developed in-house by our sister company (Vidiwave limited) – the WIMS module.
WIMS uses an AES-256 bit encrypted VPN tunnel to protect data sent to our cloud-based analytics server Vidimon-IQ.
To ensure data is handled in as near real-time as possible WIMS supports both 3G and WLAN data back up to designated remote FTP’s like VidimonIQ.

The third and final step to solving the problem was to find a way of making sense of all the data collected, and then distributing the results in a simple, secure, easy to understand format.

This was achieved again by re-using two existing technologies from our sister company (Vidiwave Limited) – Vidimon-IQ & Vidi-Cloud.
Vidimon-IQ is a very powerful on-line Condition Monitoring and Alerting server that sits with-in the Vidiwave VPN infrastructure on the cloud protected by a full SSL firewall. In simple terms, it analyses all the data against pre-set pass/fail criteria’s agreed with the train operators. Anything that fails is flagged up in real-time and the information is relayed to the client for action.
Vidi-Cloud is a secure hosted web-portal that provides the operator secure access to:
- Real-time fuel performance logs
- Real-time service and maintenance logs
- Alert history and response logs
- Historical fuel performance and maintenance reliability reports

The two key advantages of the VFT solution are:

the operator can see the fuel performance results in real-time rather than waiting the traditional 6-months before they are able analyse and action a fleet roll out. This helps them to maximise the savings available during the life of the franchise for shareholders.
All the variables mentioned above that had previously been ignored because they were simply impossible to collect, are now included and therefore factored in.

If information is power, then VFT’s remote analytics is at the pinnacle of delivering that power to give you more information than you have ever been able to acquire.

For more information on how we can help you develop a tailored fuel solution, please contact us at:info@vidiwavefueltechnology.com