Would you all like to see ISO 4548-12 Oil Filter Lab Testing Comparison, Efficiency & Capacity, Pressure vs Flow, Bubble Point, and Burst?

[Job]

Like said before, it also depends a lot on the OCI. If someone is doing a 3-5K OCI then a high efficiency oil filter isn't as important. For a short OCI, I'd still go for a filter that's at least 90% @20u. The way I see it is why not pay a few bucks more for a high efficiency oil filter that gets changed once a year. One less street taco for lunch over a years time, and it pays for a better oil filter.


As long as I own the vehicle, keeping the engine "pristine" is a goal. If it gets wrecked or sold then it's out of my hands, but I don't treat my vehicles based on looking way into the future and say: "I don't care how I treat or take care of it because someday I won't own it anymore".

That’s why I had some Frantz’s. I am glad you are so sure of things. Not sure where you put real world particle counts, but hey it’s not my house.

 

[ZeeOSix]

That’s why I had some Frantz’s. I am glad you are so sure of things. Not sure where you put real world particle counts, but hey it’s not my house.

Where I "put real world particle counts" is not in my oil by using better efficiency filters.

 

[adams355]

Any idea how much actual GPM that oil pump puts out at 6000 RPM? Looking at the delta-p vs flow curves, the Ultra was in the good flowing filter group. The fluid Andrew used for the delta-p vs flow testing was about the same hot viscosity as xW-40 weight oil - it was mentioned earlier in this thread.

9-11 GPM at best guess. Will confirm when I can get some more details. I don't think its anything wild though.

Is there a date code on the Purolator Boss seems strange it wouldn't meet its specs.

Clean oil also equals more horsepower. And turbo's don't last as long as engines in most reality's unless very well looked after.

 

[dnewton3]

No test is perfect. ...
I do not have an opinion on the GM studies accuracy. I think of it as just another indicator that better filtration is a good idea.

I would agree that no test is perfect. But I would counter with the fact that there can be much better studies done when real life is taken into account. It's just that most folks who do have the interest in doing so, don't have the time/money because the burden of proof comes from large quantities of data. Companies, OTOH, whom do have much deeper pockets, don't have the inclination to be patient; they want a fast return on the investment and not wait for long periods of time.

When a ALT/HALT test process is used, it can be a good indication of how things perform, one relative to another. But that relativity stops when you try to quantify it to "normal" daily use of something.
Example:
We have salt-spray chambers at work. They are used to induce corrosion effects when we test different materials which would be in our products in coastal conditions (near the oceans and gulf). What we can do is test product A against product B, and then conclude that A is either better, same, or worse than B. But we cannot say with impunity and assurance that A is going to last "XXXX" hours longer in real life. Product A may have lasted "yyy" hours longer in salt-spray than B did (to a predetermined state of some characteristic), but there's no way for us to say "yyy" hours in the lab equals "xxx" hours in the field, because we've never spent the time/money to find the correlation between those two.

For the GM filter study to be accurate and useful to us common weekend garage-wrencher types, we'd need GM to show accurate correlation that "xxx" hours in their test = "yyyy" miles on my odometer. They'd have to take their data from the lab test, and then do field testing to establish a ratio of lab hours to typical miles driven. They never did that, and in fact they knew darn good and well that the wear rates they induced were so absurdly high that there's no way they'd be able to recreate the same effect in the field. Hence their disclaimer statement.

To be a well conducted test, you want to remove or control as many variables as possible, so that you can manipulate the desired input in an "on/off" method, such that results can be attributed to the controlled input and not other uncontrolled things. By choosing to never change oil during the filter study, GM eliminated OCIs as a variable input. They held the OCI constant (never changed oil), and the controlled variables were filter pore size, filter pressure differential to indicate change needed, and particulate loading rate.

In fact, the particulate loading rate is even absurd. Not just in it's quantity, but in it's introduction. They didn't meter the dust in, they just dumped it in once an hour. That would be akin to you and I deciding to remove our air filter, then go do a bunch of wheel-ripping donuts in a dusty empty bean field, right after we change oil. They rate of particulate induction wasn't a small constant stream; it was a massive overloading at the top of each hour!




Conversely, there are "tests" which do exist which give an excellent indication of how well or poorly products last in our vehicles. We have anecdotal evidence (reasonably documented stories which establish results, but don't necessarily have a lot of data), and we have data from actual use (UOAs, PCs, etc).

UOAs are NOT perfect, either. But they are a representative look at the way wear presents itself over time. UOAs most certainly do have limitations, but just like any other tool, if you understand those limitations, you have a good chance of knowing what the data can and cannot tell you.

Want to enjoy a little sliver of irony? The GM filter study used spectral analysis to determine relative rates of wear, along with other methods, in their HALT results. But then they didn't want to invest the time/money of using UOAs to determine how those lab tests correlated to the real world! Kind of ironic, is it not? They can accurately claim that the 7um filter extends a project lifecycle 7x greater than the 40um filter, but ONLY under the conditions of the test. Once those conditions are no longer true, the test results are no longer true!!!

If GM had changed the oil during their tests every 4.2 minutes, AND introduced the particulate loading in a metered manner such that the loading effects were managed by the simulated mileage rates, THEN AND ONLY THEN would the GM filter study have merit in our garages. But ... GM knew that such efforts would bring forth such incredibly tiny, fractional differences that they would have no ability whatsoever to discern filtration effects. Why? Because the oil filter is not the only entity controlling wear during normal maintenance of an engine. OCIs and TCBs are also major contributors to the wear rate control.

Most simply put, the GM filter study is completely and utterly useless to establish any kind of meaningful representation of what happens in our engines in the daily lives of any typical Joe Average vehicle owner.


- What we know anecdotally is that there are LOTS of vehicles which run 200k-300k with just "normal" oils and filters.
- We also know that UOAs can show us that wear rates due to full-flow filter selection are moot; the amount normal wear variation trumps the "noise" of filter selection in statistical analysis.

YES, ABSOLUTELY, filtration is important. It's VERY important. But only to a point. After that point, the effect of filtration is overtaken by the OCI duration and the TCB. In fact, those three things act in concert together (filter, OCI, TCB) to reduce wear, and it's very difficult to test one without giving credit where due to the others.

The longer an OCI is run, the greater the need for better filters. The shorter the OCI is run, the less important filtration is. That, in a nutshell, is the (unmentioned) lesson to glean from the GM filter study. Anyone who practices "normal" oil changes, is NEVER, EVER going to see a tangible and meaningful shift in their wear rates simply because they chose one filter over another, presuming the filters they pick from are approved for the application. The effect of filter selection is so incredibly small in a normal OCI that there is no way at all it can be discerned in real life. And GM even admitted that fact in their conclusion statements; they truthfully admitted that the results from their lab study will never be seen in real life because what they did is not practiced in your garage.

HALTs are meaningful for relative performance delineation only. The results are NOT transferable to real life, unless there is a subsequent correlation study done to show xxx lab hours = yyy life hours (miles, or whatever UoM is chosen). In this particular case, GM chose not to do that correlation study, because they knew they'd never be able to generate enough wear to show the wear rates were statistically significantly different in normal operation above the noise of normal wear patterns. Why? Because oil changes flush out the particulate loading soon enough that filter choices don't matter. It's incredibly important to have a filter in place. It's not nearly as important to worry about filter A having 80% efficiency at Xum over filter B having 95% efficiency at that same size. Or 95% versus 99%; even less so.

Once a filter's efficiency is "good enough", making it better has no real effect. I cannot tell you what "good enough" is; there's no study done that I know of that credibly establishes that level. But, there are tens of millions of cars driving around every day that anecdotally tell us that "good enough" already exists on the shelf of every parts store in North America.


My long winded point to all this? Ignore the GM filter study, unless you never, ever change oil at all and drive around in a dusty bean field all day, every day, 365 days a year, with no air filter in place.

 

[Ascent Filtration Testing]

I would agree that no test is perfect. But I would counter with the fact that there can be much better studies done when real life is taken into account. It's just that most folks who do have the interest in doing so, don't have the time/money because the burden of proof comes from large quantities of data. Companies, OTOH, whom do have much deeper pockets, don't have the inclination to be patient; they want a fast return on the investment and not wait for long periods of time.

When a ALT/HALT test process is used, it can be a good indication of how things perform, one relative to another. But that relativity stops when you try to quantify it to "normal" daily use of something.
Example:
We have salt-spray chambers at work. They are used to induce corrosion effects when we test different materials which would be in our products in coastal conditions (near the oceans and gulf). What we can do is test product A against product B, and then conclude that A is either better, same, or worse than B. But we cannot say with impunity and assurance that A is going to last "XXXX" hours longer in real life. Product A may have lasted "yyy" hours longer in salt-spray than B did (to a predetermined state of some characteristic), but there's no way for us to say "yyy" hours in the lab equals "xxx" hours in the field, because we've never spent the time/money to find the correlation between those two.

For the GM filter study to be accurate and useful to us common weekend garage-wrencher types, we'd need GM to show accurate correlation that "xxx" hours in their test = "yyyy" miles on my odometer. They'd have to take their data from the lab test, and then do field testing to establish a ratio of lab hours to typical miles driven. They never did that, and in fact they knew darn good and well that the wear rates they induced were so absurdly high that there's no way they'd be able to recreate the same effect in the field. Hence their disclaimer statement.

To be a well conducted test, you want to remove or control as many variables as possible, so that you can manipulate the desired input in an "on/off" method, such that results can be attributed to the controlled input and not other uncontrolled things. By choosing to never change oil during the filter study, GM eliminated OCIs as a variable input. They held the OCI constant (never changed oil), and the controlled variables were filter pore size, filter pressure differential to indicate change needed, and particulate loading rate.

In fact, the particulate loading rate is even absurd. Not just in it's quantity, but in it's introduction. They didn't meter the dust in, they just dumped it in once an hour. That would be akin to you and I deciding to remove our air filter, then go do a bunch of wheel-ripping donuts in a dusty empty bean field, right after we change oil. They rate of particulate induction wasn't a small constant stream; it was a massive overloading at the top of each hour!




Conversely, there are "tests" which do exist which give an excellent indication of how well or poorly products last in our vehicles. We have anecdotal evidence (reasonably documented stories which establish results, but don't necessarily have a lot of data), and we have data from actual use (UOAs, PCs, etc).

UOAs are NOT perfect, either. But they are a representative look at the way wear presents itself over time. UOAs most certainly do have limitations, but just like any other tool, if you understand those limitations, you have a good chance of knowing what the data can and cannot tell you.

Want to enjoy a little sliver of irony? The GM filter study used spectral analysis to determine relative rates of wear, along with other methods, in their HALT results. But then they didn't want to invest the time/money of using UOAs to determine how those lab tests correlated to the real world! Kind of ironic, is it not? They can accurately claim that the 7um filter extends a project lifecycle 7x greater than the 40um filter, but ONLY under the conditions of the test. Once those conditions are no longer true, the test results are no longer true!!!

If GM had changed the oil during their tests every 4.2 minutes, AND introduced the particulate loading in a metered manner such that the loading effects were managed by the simulated mileage rates, THEN AND ONLY THEN would the GM filter study have merit in our garages. But ... GM knew that such efforts would bring forth such incredibly tiny, fractional differences that they would have no ability whatsoever to discern filtration effects. Why? Because the oil filter is not the only entity controlling wear during normal maintenance of an engine. OCIs and TCBs are also major contributors to the wear rate control.

Most simply put, the GM filter study is completely and utterly useless to establish any kind of meaningful representation of what happens in our engines in the daily lives of any typical Joe Average vehicle owner.


- What we know anecdotally is that there are LOTS of vehicles which run 200k-300k with just "normal" oils and filters.
- We also know that UOAs can show us that wear rates due to full-flow filter selection are moot; the amount normal wear variation trumps the "noise" of filter selection in statistical analysis.

YES, ABSOLUTELY, filtration is important. It's VERY important. But only to a point. After that point, the effect of filtration is overtaken by the OCI duration and the TCB. In fact, those three things act in concert together (filter, OCI, TCB) to reduce wear, and it's very difficult to test one without giving credit where due to the others.

The longer an OCI is run, the greater the need for better filters. The shorter the OCI is run, the less important filtration is. That, in a nutshell, is the (unmentioned) lesson to glean from the GM filter study. Anyone who practices "normal" oil changes, is NEVER, EVER going to see a tangible and meaningful shift in their wear rates simply because they chose one filter over another, presuming the filters they pick from are approved for the application. The effect of filter selection is so incredibly small in a normal OCI that there is no way at all it can be discerned in real life. And GM even admitted that fact in their conclusion statements; they truthfully admitted that the results from their lab study will never be seen in real life because what they did is not practiced in your garage.

HALTs are meaningful for relative performance delineation only. The results are NOT transferable to real life, unless there is a subsequent correlation study done to show xxx lab hours = yyy life hours (miles, or whatever UoM is chosen). In this particular case, GM chose not to do that correlation study, because they knew they'd never be able to generate enough wear to show the wear rates were statistically significantly different in normal operation above the noise of normal wear patterns. Why? Because oil changes flush out the particulate loading soon enough that filter choices don't matter. It's incredibly important to have a filter in place. It's not nearly as important to worry about filter A having 80% efficiency at Xum over filter B having 95% efficiency at that same size. Or 95% versus 99%; even less so.

Once a filter's efficiency is "good enough", making it better has no real effect. I cannot tell you what "good enough" is; there's no study done that I know of that credibly establishes that level. But, there are tens of millions of cars driving around every day that anecdotally tell us that "good enough" already exists on the shelf of every parts store in North America.


My long winded point to all this? Ignore the GM filter study, unless you never, ever change oil at all and drive around in a dusty bean field all day, every day, 365 days a year, with no air filter in place.

I appreciate your opinion on this subject. This study appears to be deeply flawed. Thank you very much.

 

[Job]

Where I "put real world particle counts" is not in my oil by using better efficiency filters.

Try looking under the rug where you swept them. Whole lot of it piled up under there.

 

[Davejam]

Thing is ... the WIX XP is touted as a long OCI filter. But as the data shows, the more it gets loaded up the worse the efficiency becomes. That's most likely why the overall ISO efficiency is so low at 20u.

Here's the AC Delco's original data table and your graph put together.

I've had a chance to peek at the rest of the data and can say that for all filters efficiency dropped off with run time/filter loading.
There were a few instances where efficiency increased after loading, but it wasn't sustantial, and the best efficiency was always at the low end of loading.
Generally, the way the efficiency dropped off was the same as the general data trend and the rankings wouldn't change if you focused on a smaller portion of the test.

I used to be a believer that a filter should perform better as it is used. This test has changed my opinion on that.
Though in the case of Fram Ultra it was quite good from start to finish and I wouldn't sweat using it for extended OCI.

 

[Davejam]

On average loading, it’s been mentioned many times that motorking, who used to be with Fram stated 1 gram per 1000 miles. I probably am the one always mentioning it. Which fits somewhat with mileage recommendations. Two grams is representing 2000 miles by that average.

This seems high...because the Fram Ultra is rated for 20,000 mi but in this test went to 13.6 grams. It could have gone further, but delta P is really taking off, so not much further.
I just cant imagine that much wear...but again I have nothing to base this on.
Maybe 1g/1000mi is a good universal average, where the universe is not as dilligent as BITOG member?
So half that is more likely in a well maintained engine?

Anyone have a reference on this subject? Seems like a critical aspect in interpreting these tests.

 

[kschachn]

This seems high...because the Fram Ultra is rated for 20,000 mi but in this test went to 13.6 grams. It could have gone further, but delta P is really taking off, so not much further.
I just cant imagine that much wear...but again I have nothing to base this on.
Maybe 1g/1000mi is a good universal average, where the universe is not as dilligent as BITOG member?
So half that is more likely in a well maintained engine?

Anyone have a reference on this subject? Seems like a critical aspect in interpreting these tests.

It cannot be wear. If an engine is losing 1 gram of metal per 1000 miles somewhere in the engine that engine isn't going to be running very long. It has to be mostly carbon compounds of some sort.

I struggle with the notion there could be that much of anything being trapped in the filter unless the engine isn't operating properly or is very worn.

 

[ZeeOSix]

I've had a chance to peek at the rest of the data and can say that for all filters efficiency dropped off with run time/filter loading.
There were a few instances where efficiency increased after loading, but it wasn't sustantial, and the best efficiency was always at the low end of loading.
Generally, the way the efficiency dropped off was the same as the general data trend and the rankings wouldn't change if you focused on a smaller portion of the test.

The Ultra barely dropped in efficiency as it loaded up. Part of the reason why the efficiency stays constant at an specific particle size with loading (increased delta-p) on an oil filter is because the media doesn't allow already captured particles to break way and go downstream. If media can't hold already captured particles very well as the delta-p increases from loading (or just the delta-p from the oil flow on a clean filter), then more and more particles are going to be released as it loads up, and that hurts the downstream efficiency.

I've also seen data where if a loaded filter had a constant flow of oil going through it, then all of a sudden a big spike increase in flow volume hit the filter and caused a big delta-p spike, the filter media would release a bunch of already captured debris from that delta-p spike.

I used to be a believer that a filter should perform better as it is used. This test has changed my opinion on that.
Though in the case of Fram Ultra it was quite good from start to finish and I wouldn't sweat using it for extended OCI.

Air filters seem to always get more efficient as they load up ... but oil filters typically don't. That's because the delta-p across an air filter is basically zero compared to the delta-p across an oil filter. If you put many PSI of delta-p across an air filter it would also start shedding off already captured particles.

 

[Job]

I would agree that no test is perfect. But I would counter with the fact that there can be much better studies done when real life is taken into account. It's just that most folks who do have the interest in doing so, don't have the time/money because the burden of proof comes from large quantities of data. Companies, OTOH, whom do have much deeper pockets, don't have the inclination to be patient; they want a fast return on the investment and not wait for long periods of time.

When a ALT/HALT test process is used, it can be a good indication of how things perform, one relative to another. But that relativity stops when you try to quantify it to "normal" daily use of something.
Example:
We have salt-spray chambers at work. They are used to induce corrosion effects when we test different materials which would be in our products in coastal conditions (near the oceans and gulf). What we can do is test product A against product B, and then conclude that A is either better, same, or worse than B. But we cannot say with impunity and assurance that A is going to last "XXXX" hours longer in real life. Product A may have lasted "yyy" hours longer in salt-spray than B did (to a predetermined state of some characteristic), but there's no way for us to say "yyy" hours in the lab equals "xxx" hours in the lab, because we've never spent the time/money to find the correlation between those two.

For the GM filter study to be accurate and useful to us common weekend garage-wrencher types, we'd need GM to show accurate correlation that "xxx" hours in their test = "yyyy" miles on my odometer. They'd have to take their data from the lab test, and then do field testing to establish a ratio of lab hours to typical miles driven. They never did that, and in fact they knew darn good and well that the wear rates they induced were so absurdly high that there's no way they'd be able to recreate the same effect in the field. Hence their disclaimer statement.

To be a well conducted test, you want to remove or control as many variables as possible, so that you can manipulate the desired input in an "on/off" method, such that results can be attributed to the controlled input and not other uncontrolled things. By choosing to never change oil during the filter study, GM eliminated OCIs as a variable input. They held the OCI constant (never changed oil), and the controlled variables were filter pore size, filter pressure differential to indicate change needed, and particulate loading rate.

In fact, the particulate loading rate is even absurd. Not just in it's quantity, but in it's introduction. They didn't meter the dust in, they just dumped it in once an hour. That would be akin to you and I deciding to remove our air filter, then go do a bunch of wheel-ripping donuts in a dusty empty bean field, right after we change oil. They rate of particulate induction wasn't a small constant stream; it was a massive overloading at the top of each hour!




Conversely, there are "tests" which do exist which give an excellent indication of how well or poorly products last in our vehicles. We have anecdotal evidence (reasonably documented stories which establish results, but don't necessarily have a lot of data), and we have data from actual use (UOAs, PCs, etc).

UOAs are NOT perfect, either. But they are a representative look at the way wear presents itself over time. UOAs most certainly do have limitations, but just like any other tool, if you understand those limitations, you have a good chance of knowing what the data can and cannot tell you.

Want to enjoy a little sliver of irony? The GM filter study used spectral analysis to determine relative rates of wear, along with other methods, in their HALT results. But then they didn't want to invest the time/money of using UOAs to determine how those lab tests correlated to the real world! Kind of ironic, is it not? They can accurately claim that the 7um filter extends a project lifecycle 7x greater than the 40um filter, but ONLY under the conditions of the test. Once those conditions are no longer true, the test results are no longer true!!!

If GM had changed the oil during their tests every 4.8 minutes, AND introduced the particulate loading in a metered manner such that the loading effects were managed by the simulated mileage rates, THEN AND ONLY THEN would the GM filter study have merit in our garages. But ... GM knew that such efforts would bring forth such incredibly tiny, fractional differences that they would have no ability whatsoever to discern filtration effects. Why? Because the oil filter is not the only controlling element of wear during normal maintenance of an engine. OCIs and TCBs are also major contributors to the wear rate control.

Most simply put, the GM filter study is completely and utterly useless to establish any kind of meaningful representation of what happens in our engines in the daily lives of any typical Joe Average vehicle owner.


- What we know anecdotally is that there are LOTS of vehicles which run 200k-300k with just "normal" oils and filters.
- We also know that UOAs can show us that wear rates due to full-flow filter selection are moot; the amount normal wear variation trumps the "noise" of filter selection in statistical analysis.

YES, ABSOLUTELY, filtration is important. It's VERY important. But only to a point. After that point, the effect of filtration is overtaken by the OCI duration and the TCB. In fact, those three things act in concert together (filter, OCI, TCB) to reduce wear, and it's very difficult to test one without giving credit where due to the others.

The longer an OCI is run, the greater the need for better filters. The shorter the OCI is run, the less important filtration is. That, in a nutshell, is the (unmentioned) lesson to glean from the GM filter study. Anyone who practices "normal" oil changes, is NEVER, EVER going to see a tangible and meaningful shift in their wear rates simply because they chose one filter over another, presuming the filters they pick from are approved for the application. The effect of filter selection is so incredibly small in a normal OCI that there is no way at all it can be discerned in real life. And GM even admitted that fact in their conclusion statements; they truthfully admitted that the results from their lab study will never be seen in real life because what they did is not practiced in your garage.

HALTs are meaningful for relative performance delineation only. The results are NOT transferable to real life, unless there is a subsequent correlation study done to show xxx lab hours = yyy life hours (miles, or whatever UoM is chosen). In this particular case, GM chose not to do that correlation study, because they knew they'd never be able to generate enough wear to show the wear rates were statistically significantly different in normal operation above the noise of normal wear patterns. Why? Because oil changes flush out the particulate loading soon enough that filter choices don't matter. It's incredibly important to have a filter in place. It's not nearly as important to worry about filter A having 80% efficiency at Xum over filter B having 95% efficiency at that same size. Or 95% versus 99%; even less so.

Once a filter's efficiency is "good enough", making it better has no real effect. I cannot tell you what "good enough" is; there's no study done that I know of that credibly establishes that level. But, there are tens of millions of cars driving around every day that anecdotally tell us that "good enough" already exists on the shelf of every parts store in North America.


My long winded point to all this? Ignore the GM filter study, unless you never, ever change oil at all and drive around in a dusty bean field all day, every day, 365 days a year, with no air filter in place.

This seems high...because the Fram Ultra is rated for 20,000 mi but in this test went to 13.6 grams. It could have gone further, but delta P is really taking off, so not much further.
I just cant imagine that much wear...but again I have nothing to base this on.
Maybe 1g/1000mi is a good universal average, where the universe is not as dilligent as BITOG member?
So half that is more likely in a well maintained engine?

Anyone have a reference on this subject? Seems like a critical aspect in interpreting these tests.

Let's say 1000 miles is 40 hours of engine running. One gram added evenly over 40 hours is almost invisible by the hour, let alone minute. It's not a one gram little pile thrown in, which in itself is small, it has to divided up over the 1000 miles. 1/1000 of a gram per mile. If that mile is one minute of engine running, the 1/1000 of a gram is circulating through the filter maybe three times, every 20 seconds. How that can be measured as to efficiency I don't know. It seems it would be more random catching of the particles according to their "luck."

 

[ZeeOSix]

It cannot be wear. If an engine is losing 1 gram of metal per 1000 miles somewhere in the engine that engine isn't going to be running very long. It has to be mostly carbon compounds of some sort.

Yep, I'd say mostly combustion blow-by. We've all seen C&P photos of filters in this forum showing filters ran for a normal OCI that has a bunch of crud caught in the media and dirty side of the can. Of course, the level of contamination getting into the oil depends on a lot of factors.

There is however also metal wear from engine parts rubbing on each other, as any magnetic drain plug or a FilterMag or similar magnet on the side of the oil filter can will show.

 

[Davejam]

The Ultra barely dropped in efficiency as it loaded up. Part of the reason why the efficiency stays constant at an specific particle size with loading (increased delta-p) on an oil filter is because the media doesn't allow already captured particles to break way and go downstream. If media can't hold already captured particles very well as the delta-p increases from loading (or just the delta-p from the oil flow on a clean filter), then more and more particles are going to be released as it loads up, and that hurts the downstream efficiency.

I've also seen data where if a loaded filter had a constant flow of oil going through it, then all of a sudden a big spike increase in flow volume hit the filter and caused a big delta-p spike, the filter media would release a bunch of already captured debris from that delta-p spike.


Air filters seem to always get more efficient as they load up ... but oil filters typically don't. That's because the delta-p across an air filter is basically zero compared to the delta-p across an oil filter. If you put many PSI of delta-p across an air filter it would also start shedding off already captured particles.

In this test delta P was fairly flat for 0-10min in almost every case (and 0-15min for some filters), but efficiency was dropping over the same period.
If what you're saying is the case you'd see a more direct correlation between efficiency and delta P. And efficiency would drop off a cliff towards the end when delta P takes off (this wasn't the case).
What you're saying is logical, but I don't believe the data supports it.

It cannot be wear. If an engine is losing 1 gram of metal per 1000 miles somewhere in the engine that engine isn't going to be running very long. It has to be mostly carbon compounds of some sort.

I struggle with the notion there could be that much of anything being trapped in the filter unless the engine isn't operating properly or is very worn.

True. And i'm still struggling with the notion as well.
1000mi would at least make Fram Ultra's 20k mi claim reasonable. And based on these results, who would question anything Fram claimed, lol.

 

[ZeeOSix]

In this test delta P was fairly flat for 0-10min in almost every case (and 0-15min for some filters), but efficiency was dropping over the same period.
If what you're saying is the case you'd see a more direct correlation between efficiency and delta P. And efficiency would drop off a cliff towards the end when delta P takes off (this wasn't the case).
What you're saying is logical, but I don't believe the data supports it.

Here are the two graphs that show that the Ultra hardly lost any efficiency right up to where Andrew stopped the test - the point during the test run where he decided the delta-p and capacity hit the limit he set. That's why some filters could go longer in the test than others while being hit with the same level of test dust loading. Some filters have more holding capacity, so it takes longer for them to reach the defined end of test parameters.

The efficiency curve reflects the entire test run from start to finish for each filter. The efficiency vs particle size graph takes into account the average efficiency over the test run at each particle size. The tabular data would show how the filter lost efficiency at each particle size as it loaded up during the test duration (like for the AC Delco filter in Post #388 ). Andrew would have to post the tabular data for the Ultra to see more clearly how it's losing efficiency at every particle size as the test time increases.

 

[ZeeOSix]

9-11 GPM at best guess. Will confirm when I can get some more details. I don't think its anything wild though.

Based on the delta-p vs flow curve that the ISO testing found for the Ultra, 11 GPM = 41.7 LPM. The delta-p with hot oil that is what a xxW-40 would be (as used in this test) looks like around 230 in-H2O = 8.3 PSI. If you're running xxW-50 oil, then add a little more delta-p ... call it 9-10 PSI max at 11 GPM, assuming the filter you're using is similar in size to the one tested here. Compare that to the opening PSI of the bypass valve on the Ultra for that engine.

 

[Davejam]

Here are the two graphs that show that the Ultra hardly lost any efficiency right up to where Andrew stopped the test - the point during the test run where he decided the delta-p and capacity hit the limit he set. That's why some filters could go longer in the test than others while being hit with the same level of test dust loading. Some filters have more holding capacity, so it takes longer for them to reach the defined end of test parameters.

I posted the efficiency of AC Delco dropping off with time, basically immediately before a significant change in delta P.
Here's another look at what I'm saying: Efficiency drops off linearly but pressure drop is not linear.

The efficiency curve reflects the entire test run from start to finish for each filter. The efficiency vs particle size graph takes into account the average efficiency over the test run at each particle size. The tabular data would show how the filter lost efficiency at each particle size as it loaded up during the test duration (like for the AC Delco filter in Post #388 ). Andrew would have to post the tabular data for the Ultra to see more clearly how it's losing efficiency at every particle size as the test time increases.

I was able to make the graph above from information already posted. I've looked at Fram data privately and both delta P and efficiency follow similar trends (though the Fram efficiency remains at 99+% so the slope is much different (but still linear)). So I would assume each filter will behave similarly in this regard.

 

[ZeeOSix]

I posted the efficiency of AC Delco dropping off with time, basically immediately before a significant change in delta P.
Here's another look at what I'm saying: Efficiency drops off linearly but pressure drop is not linear.
View attachment 59779

I was able to make the graph above from information already posted. I've looked at Fram data privately and both delta P and efficiency follow similar trends (though the Fram efficiency remains at 99+% so the slope is much different (but still linear)). So I would assume each filter will behave similarly in this regard.

Good plot of the tabular data that shows the start of the "hockey stick" efficiency curve, which basically all these tested filters have, including the Ultra to a very minor degree. If the tests were ran longer, the efficiency would go back up again right before the filter almost totally clogged up, similar to the H+M/Purolator test data showed in post #393.

But the drop in efficiency of the Ultra as the delta-p increases is basically nothing compared to the other filters in the test group. That's why the overall ISO efficiency rating on the Ultra is so high at 20u (99+%). If all the filters' efficiency vs delta-p data at each particle size tested were plottoed on the same scale, it would show the Ultra hardly changed efficiency throughout the entire test run as its delta-p increased.

@Ascent Filtration Testing , since you own the data, if you could post the tabular data for the Ultra then the graphed data like @Davejam posted above for the ACDelco could be put on the same graph for comparison - since he's already got Excel going to do data plots.

 

[Ascent Filtration Testing]

I posted the efficiency of AC Delco dropping off with time, basically immediately before a significant change in delta P.
Here's another look at what I'm saying: Efficiency drops off linearly but pressure drop is not linear.
View attachment 59779


I was able to make the graph above from information already posted. I've looked at Fram data privately and both delta P and efficiency follow similar trends (though the Fram efficiency remains at 99+% so the slope is much different (but still linear)). So I would assume each filter will behave similarly in this regard.

Good plot of the tabular data that shows the start of the "hockey stick" efficiency curve, which basically all these tested filters have, including the Ultra to a very minor degree. If the tests were ran longer, the efficiency would go back up again right before the filter almost totally clogged up, similar to the H+M/Purolator test data showed in post #393.

But the drop in efficiency of the Ultra as the delta-p increases is basically nothing compared to the other filters in the test group. That's why the overall ISO efficiency rating on the Ultra is so high at 20u (99+%). If all the filters' efficiency vs delta-p data at each particle size tested were plottoed on the same scale, it would show the Ultra hardly changed efficiency throughout the entire test run as its delta-p increased.

@Ascent Filtration Testing , since you own the data, if you could post the tabular data for the Ultra then the graphed data like @Davejam posted above for the ACDelco could be put on the same graph for comparison - since he's already got Excel going to do data plots.

Good plot of the tabular data that shows the start of the "hockey stick" efficiency curve, which basically all these tested filters have, including the Ultra to a very minor degree. If the tests were ran longer, the efficiency would go back up again right before the filter almost totally clogged up, similar to the H+M/Purolator test data showed in post #393.

But the drop in efficiency of the Ultra as the delta-p increases is basically nothing compared to the other filters in the test group. That's why the overall ISO efficiency rating on the Ultra is so high at 20u (99+%). If all the filters' efficiency vs delta-p data at each particle size tested were plottoed on the same scale, it would show the Ultra hardly changed efficiency throughout the entire test run as its delta-p increased.

@Ascent Filtration Testing , since you own the data, if you could post the tabular data for the Ultra then the graphed data like @Davejam posted above for the ACDelco could be put on the same graph for comparison - since he's already got Excel going to do data plots.

Unfortunately I can't until after the 16th of this month. I have been converting my PDF files to photos JPEG and tried about 10 different ways and the resolution is to blurry. The AC-DeI I did show was a clipped pic from excel, which I don't like because it does not show the full page of the report.

 

[garageman402]

I am, but I got Covid and a hurting unit at the moment. I am 6 days in. Fever 102.1F. Please bear with me.

Wow, sorry to hear that, hope you make a complete recovery!!

Thanks for posting what you did, the dismal performance of the pbl22500 is a major letdown for me. Looks like I'm back to Fram, haven't used Fram products in 20 years, looks like I've been converted.....

 

[Ascent Filtration Testing]

Wow, sorry to hear that, hope you make a complete recovery!!

Thanks for posting what you did, the dismal performance of the pbl22500 is a major letdown for me. Looks like I'm back to Fram, haven't used Fram products in 20 years, looks like I've been converted.....

I am doing much better now thanks, and trying to play catch up for work. 3rd video soon!