Neural network controller for internal combustion engine

In summary, Jaco, neural nets might be a good choice for this application if you can justify why they might be better than a standard PID controller. They can be more accurately tuned and keep the temperature more stable over time.
  • #1
Jaco
1
0
I'm currently doing a project on neural network controller for an internal combustion engine to reduce emissions level. Can anyone assist me in training such models (neural networks)
 
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  • #2
What's the advantage of using a neural network in this situation? It seems to me a standard PID loop is perfectly sufficient...
 
  • #3
Mech_Engineer said:
What's the advantage of using a neural network in this situation? It seems to me a standard PID loop is perfectly sufficient...

Perhaps a neural network can be trained to optimize PID gains.
 
  • #4
Most halfway decent PID controllers are self-tuing. Your car already does this.
 
  • #5
russ_watters said:
Most halfway decent PID controllers are self-tuing. Your car already does this.

Cars are self-tuning, how do they do this?
 
  • #6
Cyrus said:
Cars are self-tuning, how do they do this?
For starters, by keeping track of operating parameters and matching the next one to the previously logged parameters. How much further it goes beyond that, I'm not sure, but a home thermostat does similar things. It keeps track of overshoot and adjusts the timings to compensate.
Digital thermostats with PID controller
More expensive models have a built-in PID controller, so that the thermostat knows ahead how the system will react to its commands. For instance, setting it up that temperature in the morning at 7am should be 21 degrees, makes sure that at that time the temperature will be 21 degrees (a conventional thermostat would just start working at that time). The PID controller decides at what time the system should be activated in order to reach the desired temperature at the desired time. It knows this by remembering the past behavior of the room, and the current temperature of the room.

It also makes sure that the temperature is very stable (for instance, by reducing overshoots at the end of the heating cycle) so that the comfort level is increased.
http://en.wikipedia.org/wiki/Programmable_thermostat

I'm not sure exactly how much a car's computer does, but if you've ever run the battery completely dead on your car, you may notice that it has trouble idling for a while until it figures out how to properly control the fuel/air mixture.
 
  • #7
Mmmm...I don't believe this explanation. A PID controller has a set of gains which are determined based on a linear model of the system.

All you have described is how the PID controller works, not how the controller figures out which gains to use. Perhaps they are doing gain scheduling where the map a series of gains based on the closest conditions of the system at the time, but none of these explanations talk about how it (if at all) 'figures out' what gains to use.
 
  • #8
I hope you guys do know that you aren't helping the OP one iota. And you haven't rolled out the welcome mat, either! Bad form!

That said, this is not a good opening post:
Jaco said:
I'm currently doing a project on neural network controller for an internal combustion engine to reduce emissions level. Can anyone assist me in training such models (neural networks)
So, first off, rolling out the official welcome mat: Welcome to PhysicsForums, Jaco!

Now I'm going to pick on you a bit, Jaco. Don't take it too personally. Hopefully this will help other newbies learn to phrase things a bit better (and you too, Jaco; this can be a very helpful place).

We do have some written rules here; you violated an unwritten one. A very big one, too. The rule is don't ask us to write a book. That is precisely what you have done by asking us "Can anyone assist me in training such models (neural networks)". The question is too open ended, too vague. The answer would require us to write a book on neural nets. There are in fact many books whose main topic is this very question.

So, Jaco, if you are still around, I'll help you in terms of questions. First question, very important:

What research have you done on this topic? We are a lot more willing to help students who have shown some work of their own.

Now some more questions that you should investigate during your research:
  • Why would someone want to use neural nets when conventional control theory does a bang-up job for the most part?
  • Where does conventional control theory start to unravel?
  • Are neural nets already in use in the auto industry? By whom?
 

1. What is a neural network controller for internal combustion engine?

A neural network controller for internal combustion engine is a type of artificial intelligence system that uses a network of interconnected nodes to simulate the decision-making process of the human brain. It is designed to optimize the performance of an internal combustion engine by learning from data and making adjustments to various parameters in real-time.

2. How does a neural network controller for internal combustion engine work?

A neural network controller for internal combustion engine works by taking input from various sensors that monitor engine performance, such as temperature, pressure, and fuel consumption. This data is then fed into the neural network, which uses algorithms to analyze the data and make decisions on how to adjust engine parameters, such as fuel injection timing and air-fuel ratio, to optimize performance.

3. What are the benefits of using a neural network controller for internal combustion engine?

There are several benefits to using a neural network controller for internal combustion engine. Firstly, it can improve engine performance and efficiency by constantly adjusting parameters in real-time. Secondly, it can adapt to changing conditions and learn from past data, making it more accurate and efficient over time. Additionally, it can reduce emissions and extend the lifespan of the engine by optimizing its operation.

4. Are there any limitations to using a neural network controller for internal combustion engine?

While a neural network controller for internal combustion engine has many benefits, it also has some limitations. One of the main challenges is the need for large amounts of data to train the neural network, which can be time-consuming and costly. Additionally, the complexity of the system can make it difficult to understand and troubleshoot issues if they arise.

5. Is a neural network controller for internal combustion engine widely used in the automotive industry?

Yes, neural network controllers for internal combustion engines are becoming increasingly popular in the automotive industry. They are used in a variety of applications, including optimizing engine performance, controlling emissions, and improving fuel efficiency. However, their use is still relatively new and there is ongoing research and development in this area to further improve their effectiveness and reliability.

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