MoTeC ECU Traction Control (METC)

The MoTeC ECU traction controller provides an important comparison tool, and determines engine cut based on the four measured wheel speeds and any relevant engine data within the ECU. Its operational algorithm is not explicitly stated within its documentation, nor were MoTeC support willing to divulge this “commercial in confidence” material. However, and as discussed previously, the control algorithm seems to be based on a linear relationship between the amount of slip above a predetermined level to the percentage of engine cut, with a few other parameters used to provide additional “trims”. For any given track, this means that many parameters need

to be tuned repetitively for efficient operation. This is in contrast to controllers used in typical passenger vehicles because it is not generally robust across different surface conditions, but rather is tuned for maximum performance in specific conditions. In this regard, and if the MoTeC traction controller can be tuned to a high level, the MoTeC traction control can be considered to provided better performance than passenger vehicle controllers. Furthermore, because the controller can be tuned for specific conditions, it is not unreasonable to assume that it would provide near-optimal performance.

Finally, because all of the control logic and sensor inputs are housed within a purpose built and highly refined unit, the sample rate for control can be expected to be much higher than the 50Hz used for the ANN models (although this actual rate is not clear). This would increase the performance of the MoTeC traction controller further and, since all other models are limited to 50Hz, would not provide a fair performance comparison. Nonetheless, the results of MoTeC traction control tuning provide useful information with regards to optimum traction conditions and maximum achievable accelerations, and are shown in Table 8.1 (cumulative slips are calculated from the average of preceding slips), Figure 8.9 and Figure 8.10.

Table 8.1: Summary of top five METC straight-line accelerations for different aim slips

Figure 8.9: Vehicle acceleration, slip and speed for best straight-line acceleration for 3km/hr (0.83m/s)

METC

Figure 8.10: Vehicle acceleration, slip and speed for best straight-line acceleration for 10km/hr (2.8m/s)

METC

These results were obtained after many traction control tests, which sought to determine three control variables. The first two were concerned with the proportional gains of the controller, and were tuned to give smooth traction control operation. The Slip Control Range = 5km/hr and the Controller Gain = 3.6Vs/m defined the gain and engine full cut limits, and once determined were used throughout subsequent testing. Aim Slip was varied within the traction controller, and the resultant performance evaluated based on repeated runs. To simplify this analysis, testing was only conducted in straight-line tests.

Surprisingly, however, it can be seen that the aim slip seems to have little effect on the performance of the METC. In particular, both low and high slips are present in the maximum accelerations, and it is hypothesized that this is due to two reasons. The first concerns the dynamics of the vehicle at “launch”, and the second is the in observation of the oscillatory nature of the high slip control.

When the vehicle starts off at launch, maximum acceleration is not found by controlling the driven wheels to obtain optimum coefficient of friction. Instead, the limitations of the engine come into play, and it is important to keep the engine within an rpm range that produces sufficient power. Considering what happens as the vehicle first starts moving best highlights this. If the optimum coefficient of friction is at, say, 2m/s and the vehicle is at rest, then the engine must turn very slowly (without ‘dragging’ the clutch) to achieve this slip value. This would probably result in the engine stalling, or a severe drop in power at the very least. If the engine does not stall, the car will accelerate very

slowly at much less than the optimum slip until the engine speed increases to a point where sufficient power may be delivered to the wheels. Only then will “optimum” performance be realised. In contrast, spinning the wheels excessively at launch may produce similar problems. Here, the optimum slip is greatly exceeded and the acceleration is much lower than otherwise possible. In this case the vehicle will slowly accelerate until its speed increases enough to reduce the magnitude of the slip, and therefore gain additional acceleration. This type of problem falls outside of the scope of traction controllers, and is termed “Launch Control”. In fact, operating traditional traction control at very low speeds has the capacity to significantly reduce achievable accelerations. Furthermore, there is a very fine line between good and bad performance at launch, and this has large impacts on the overall acceleration of the vehicle through the straight-line acceleration test. To try and overcome this problem, a large number of tests were completed, where each one attempted to gain the maximum acceleration possible with the current traction control aim slip. However, this effect could not be removed entirely, and has affected the results to a degree.

The second potential source of variation maybe from the controller oscillation at high slips, which is highlighted in Figure 8.10. The vehicle slip oscillates around the aim slip with a large degree of variation, and results in complex vehicle dynamics. This is due to limitations within the METC tuning software that allows only a fixed gain to be tuned, even though the amount of throttle used instantaneously would have a large effect on the optimum magnitude of this value. Furthermore, the lack of integral and differential gain control makes controller oscillation very hard to avoid. Combined with the high sampling rate of the controller, this produces a very high and active control load, and ensured the tyres were constantly experiencing significant transient conditions. This made comparison to the low aim slip control difficult.

Nonetheless, when comparing Figure 8.9 and Figure 8.10, it can readily be seen which type of vehicle dynamics would be desired for smooth and efficient operation while delivering maximum performance. Furthermore the 10km/hr case has launched much better than the 3km/hr case (at lower slip), and then shown reduced acceleration during high oscillation. In contrast, the 3km/hr aim slip case exhibits better acceleration, that the controller is not very active at all, and the average slip exhibited by the car is 0.65m/s (excluding the first 5m due to “launch” effects). By averaging the top ten results together, however, the average optimum slip is 1.18m/s excluding the first 5m (from the

cumulative average slip 5m to 25m column). As such, the best average slip value is in the 0.65 to 1.93m/s range, or on an average basis to be 1.18m/s.

Lastly, the precise control of wheel slip can be used to ensure vehicle dynamics data is acquired for the full scope driving conditions. This is particularly important because, without any traction control, intermediate slips are very hard to realise on the slippery surface. As such, data can be logged for the many different slip values and utilised within ANN controller training sets. It is noted, however, that this type of data acquisition is only appropriate for ANN models that are concerned with vehicle dynamics, and if any engine data is used within the model, this method cannot be used.