Posted by: drracing | June 16, 2017

Testing suspension geometry in the simulator

Hi everybody!

As anticipated in my last post, this article will be a review of one of the project I was involved with during the winter. As for one of my latest project of 2016, also this case study is actually relative to an investigation I supported using driving simulation as a development tool, in a way I had not thought possible a few years ago. Life is full of surprises.

After during the summer I had a chance to prove myself how, even using a cheap software, a proper vehicle model could be used effectively to gain some more insight about car setup and its intricacies (helping the team I was supporting to further improve a bit their performance), this time I was asked to try to evaluate different design solutions and quantify not only their performance but also driver’s perception / feedback to each of them.
The study was focused more specifically on investigating the effects on car handling and performance of different front suspension layouts, differing sometimes pretty much one to the other (in one or more areas), with the aim to evaluated what the driver would feel driving each of them, together with their impact on the car-driver system’s performance.
The guy who asked me to support this project was initially mainly looking to understand the impact on driver steering feedback coming from different designs / geometries, but soon the study also evolved into a chance to evaluate which influence each setup would have on overall performance and why, identifying, also through data analysis, in which areas there would be the biggest differences and the reasons behind each Delta.

The model we used was actually the reliable and good validated 2016 LMP2 one, driven in Silverstone.
We starting establishing a baseline (lap time / performance and behavior) using the original design, then moving onto testing new solutions.
The parameters we worked on at the beginning were mainly scrub radius, king pin angle and caster trail, but inevitably we soon moved on also acting on camber change, roll center position and migration and caster angle and finding out how also other parameters that we underestimated at the beginning actually play an important role, at least in terms of steering feedback.

Before I dive a bit more into the details of this project, let me spend two words about the assumptions used by rFactor in terms of suspension modeling and my view about the software’s limitation.
First of all, it is clear to me, as it is probably clear to all of view, that rFactor was not though as an engineering tool and there are some limitations that are difficult to completely overcome, if not acting on the code itself (which is out of my skills, intention and interest).
I would of course be very happy to have a chance to use more “engineering” oriented and flexible software for my projects, but the budget required to buy one of them would probably be absolutely out of reach even for many small companies.
The truth is, anyway, that it is amazing how much you can test and understand, in terms of vehicle dynamics and even in terms of setup / layout even using a cheap product like rFactor, despite all of its limitations. Of course, “conditio sine qua non” is always to know exactly your assumptions and to build a model as close as possible to the real car (or at least to the data we have about it).

As we had a chance to briefly mention in one of my previous posts, rFactor simulates suspension behavior in a very advanced way, since it practically define each suspension component as a rigid body (with or without mass properties) connected to the surrounding ones through mechanical constraints, like spherical joints, hinges, etc. This means, for example, that the wheel and the “spindle” (which actually identifies the complete Upright – Hub assembly in rFactor) have their own (definable) mass and inertial properties. The links are defined as rigid elements with no mass, practically locking the distance between two points depending on their length.
There are a number of things to take care of, when modeling a suspension, including like rFactor adjust camber, caster and toe. But if these parameters remained locked or the “errors” that the software does when changing one of them are compensated in a proper way, the suspension kinematics is simulated in a very similar way to what a normal multibody package would do.
A bit of attention must be paid for layouts using a pushrod / pullrod with a rocker to activate the damper/spring unit, since the Rocker assembly and its functionality cannot be reproduced. Of course, since we are dealing with an LMP car, this is exactly the situation we find ourselves in, as we are considering a double wishbone with pushrod actuated rockers for both front and rear axle.
From a wheel rate / motion ratio perspective, this “issue” can be easily overcome producing very accurate results, as we have seen already in the past, the point here simply being to directly work with the Wheel Rates, instead of the spring rates. To do this, I am using a trick, playing with the pushrod’s hardpoints (and, consequently, with its orientation), to obtain exactly the wheel rates and wheel rates change (with respect to wheel travel) I want, independently from the rest of the kinematics.
This means that the “virtual pushrod” will have another position and another 3D orientation compared to the real one, in order to obtain the same wheel rate and wheel rate change of the real car.

From a statics perspective and, more specifically, if we want to isolate and quantify the load acting in each linkage (this is particularly important for this study, since the steering feedback was one of the parameters we would like to better understand and since rFactor and the plugins I used produce the steering wheel feedback strictly basing on the force acting on the steering tie rods), this actually can bring a difference in the results because, depending on the position and orientation of each beam, the loads acting on each of them (for a defined loadcase at the contact patch) will change. In other words, although the suspension “as a system” would still behave the same (at least considering every suspension link and the upright-hub assembly as a rigid body, so ignoring every compliance), the internal reaction forces would change.
Anyway, the good news here is that, for the suspension geometry and layout we are using, even if the absolute value of the force acting on the steering rod that could be measured in the real car is different than the one produced with our “rfactor alternative-pushrod position”, its trend and gradients are very similar: in other words, the load acting on the steering rod is changing in a similar way in both cases, for a certain change of the Fy, Fx or Fz acting at the contact patch. All of this has been checked first using a simple excel sheet I built to calculate the reaction loads in each suspension members, depending on the loadcase at the contact patch and on the pickup points position; to be absolutely sure, a second check has been done using a Multibody software and in both cases the results have shown exactly the behavior I described above.
What is important for this study is actually the trend shown by the reaction forces in the steering tie rod, since the steering forces produced by the simulator’s steering system are proportional to the steering tie rod loads through a factor that is actually what we use to tune the intensity of the steering feedback itself.

Beside the driving simulation itself, I also used some CAD and some Multibody modeling for this project; on one side, I did this to evaluate each layout before to test it with the simulator but, most often, also to tune each geometry a bit and try to isolate and change only the parameters we wanted to evaluate at each step, keeping the others as constant as possible, with the aim to limit their influence on the results (in particular the steering torques, but not only).
Anyway, in certain cases this was not actually possible because of real world physical limitations (for example parts colliding to each other) and we had to accept that, with a certain setup, some parameters that we would not want to change would indeed change (see for example Ackermann effect). It was nonetheless interesting to see how a certain set of parameters would work, both in terms of performance and driver perception.

It is probably not a case that the best performing solution was also the one which was received more enthusiastically by the driver (although, in my experience, this is unfortunately not always the case).

The first test was done using the baseline configuration, namely the front suspension geometry originally built in the car. We run some sessions with this solution and established a reference lap (and the relative logged data) to be used later as a base to evaluate the following setups both subjectively and through data analysis.

The second test was performed using a revised front suspension geometry (we will call it Exp1), mainly deviating from the baseline in the upright area. In particular, caster angle was reduced by slightly more than one degree, although the caster trail was slightly increased. The King Pin Angle was also increased by about 2 degrees, producing a smaller scrub radius. This setup also had a slightly higher Ackermann effect (more dynamic toe out) and a slightly higher roll center.
The feeling was immediately very good. The car showed a bit more understeer, above all in mid-corner and, sometimes, even in corner exit. This helps in certain situations, see for example turn 3 (a 1st gear corner, where traction is very important), but seems to be a limit in others, see for example the last chicane, above all in the exit of the second (right) corner leading to the last right tender before the box straight.
Beside showing more mid corner understeer, this setup actually also produced a more reactive behavior in corner entry, above all in quick corners.
From a driver feedback perspective, it was interesting to notice how the changes we did made the car easier to drive, giving to the driver some more confidence and also the feeling that the relationship between steering angle and front cornering forces remains more or less linear for the complete range of used angles (while the baseline had a more unpredictable behavior, above all at very high steering angles, where the cornering force seemed to drop more abruptly and in a less predictable way when exceeding with the steering angle and the driver had a feeling of “loosing front grip”), although producing more understeer.

An interesting point was the increase of steering forces, perceived by the driver and confirmed by data analysis. This seems to go somehow against the expectations of some the changes we did (see for example a reduction of caster angle).
Anyway, two factors must be considered: on one side, the caster (or longitudinal) trail was slightly longer (granting a longer lever arm to Cornering forces in producing Self aligning torques); on the other side, we noticed how, one of the side effects of the geometry change we did was a slight reduction of the length of the Steering Arm (distance between the outer tie rod point and the steering axis), thus creating a bigger force in the steering tie rod for a certain torque to be reacted.

In terms of performances, this setup produced a 3-4 tenths improvement compared to the baseline.

Here below you can see the traces relative to three logged parameters: speed, steering angle and steering force. The tested geometry is shown in red (Exp1).

Exp1 - speed

Exp1 - steering

Exp1 - steer forces

The third test (referred here as Exp2) was performed using a geometry differing from the baseline much more aggressively. Caster has been increased by about 3.5 degrees, producing also a substantially bigger caster trail (about 30% bigger than the baseline one). King Pin angle and Scrub radius were very similar to the original configuration. The Ackermann effect (or percentage or dynamic toe) was slightly lower, as was the camber gain. Finally the static roll center position was also substantially lower.

Driver’s feedback was again very good, although the car behaved very differently than in the previous test. A strong reduction of the understeering tendency was evident from the very first corners, with the front axle now having substantially more grip, above in mid-corner but also in corner exit, with a reduction of the power understeering tendency that disturbed a bit in the last chicane in the previous test. Interestingly, even showing much more front grip, the car didn’t become instable or unpredictable, nor it showed any “dangerous” oversteering behavior.
In quick corners, the vehicle was now a bit less reactive than in the previous test, but still showed very good driveability.
Steering forces increased slightly, compared to the previous test and were thus sensibly higher than the baseline setup.

The lap times we obtained were anyway very similar to the previous test, with this latest outing producing an about 0.02 seconds quicker lap time.

In the following plots, this test’s results are shown in orange (Exp2).


Exp2 - speed

Exp2 - steering

Exp2 - steer forces


The direct comparison between this setup and the previous one (not shown in these pictures) show slightly higher steering forces in this latest case, although the steering arm being now bigger than both the baseline and the first test.
To finally quantify the influence of this latest parameter we later did a very quick test using a very similar geometry compared to the one tested here, but reducing the steering arm to a very similar value compared to the baseline (and trying to keep the other parameters the same). This further increased the steering forces, making them substantially higher than both baseline and first test and, more important being a direct comparison, much bigger than this test 2.

I will not bore you with a description of all the other tests we did (some of them were not as successful as the first two and the following one) and I will just jump to the one that produced the best performances and the best driver feeling, also to show how much of a difference it did in terms of lap times and how good this could be felt in the simulator.
This latest test was performed using a front suspension geometry now having about 0.8 degrees more caster than in the previous one (and so about 4.3 degrees more than the baseline), a slightly bigger caster trail than test 2 (but much bigger than the baseline) and a smaller scrub radius (compared to both baseline and test 2), because of a sensibly bigger king pin angle. Roll center, camber gain, Ackermann effect and steering arm’s length were all kept practically the same as the baseline.
One of the interesting features of this geometry was how the camber evolves with the steering angle, not only on the outside tire but also on the inside. A caster increase normally always produce an increase of camber delta as a function of steering angle, but here this phenomenon seems to be amplified and probably also the contribution of an “effective” camber change on the inside tire helped.

Dirver’s feedback was immediately enthusiastic, as also proved by the lap times, that dropped by about 3 tenths of a second compared to the previous two tests (so overall about 7 tenths compared to the baseline).
The driver felt now even less understeer and the front axle, which ensures a very high grip, without generating oversteer or instability in any corner. The general feeling was actually of more grip on both the front and rear axle, but with even less understeer than the previous test.
This less understeering tendency could be felt also in corner exit, but somehow that didn’t deteriorate traction. The car was much easier to drive and allowed to push more easily, communicating always a feeling of stability and predictability. As a result, it was possible to go easier on the throttle on some corners’ exit, like the last chicane.
This was also true for the steering feedback: steering forces were now higher than any of the previous tests and the “linear” feeling we described about the first test remained, with the driver reporting that, even with very high steering angles, the front axle always seemed to produce cornering forces in a gradual manner, without abruptly loosing grip or generating oversteer or instability.
Interestingly, the steering trace data seems not always to confirms this strong grip of the front axle, at least compared to the baseline logged data. But it is also true that it still shows a more homogeneous use of the steering wheel, probably confirming how this more linear tendency in the relationship between steered angle and front grip and allowing the driver to maneuver the car more aggressively.

All of this seems is shown in the following plots relative to this test’s logged data, depicted in pink (Exp4).


Exp3 - speed

Exp3 - steering

Exp3 - steer forces


Beside finding extremely interesting all the tests and their outcome, I was once again amazed to see how much we can learn using (properly and also knowing the limitations and the turnaround to be used to compensate for some simplifications) a simple and cheap tool like rFactor, even from an engineering perspective.
The goodness of the results of this study is of course strongly dependent on how good also the vehicle model was built, in particular for all what concerns the tire model. I am pretty sure my model adheres pretty good to the data I have, but of course any model is only a model. Real testing is and will always be the best way to validate and decide on certain design decisions, but it is amazing to experience how much we can do in terms of pre-evaluation even with such a cheap tool.

By the way, it was really good fun to go through all these designs and also have a chance to see how they perform, getting a “more real” feeling of how the car would handle and being able to do 1:1 tests, with all the advantages connected to the use of a simulation (see deletion of the effects of track conditions, temperatures, rubbering, traffic etc).

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