The inertial parameters of a vehicle, which include the mass, centre of gravity position and the moments of inertia, influences the dynamics of the vehicle. Currently, the modelling of the vehicle is done by assuming fixed, conservative, values for the inertial parameters. Knowin
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The inertial parameters of a vehicle, which include the mass, centre of gravity position and the moments of inertia, influences the dynamics of the vehicle. Currently, the modelling of the vehicle is done by assuming fixed, conservative, values for the inertial parameters. Knowing the exact values may increase the performance, safety and comfort of the vehicle. A literature review has been conducted, where different methods for online inertial parameter estimation have been graded based on the amount of parameters it is able to estimate, the sensors used and the accuracy of the methods. Rozyn's method seems best for online inertial parameter estimation. Rozyn proposes a method which can estimate the inertial parameters from vertical acceleration data using a state variable method, modal analysis and a simple vehicle model. Rozyn's method can be summarised in four steps: •Extract the free decay response from acceleration data. •Construct the state transition matrix. •Construct the system characteristic matrix. •Estimate the inertial parameters using the constructed characteristic matrix and simplified vehicle model. The main shortcoming of Rozyn's method is the road profile which is used for the simulation, which is described in the ISO 8608 norm. The ISO 8608 description is a stationary Gaussian process. This means that the road profile random variables are normally distributed. Furthermore, the properties of the road profile (mean and variance) does not change over time. In practice however, road profiles never follow a stationary Gaussian process, but are much more random, with more variance between different sections. Another, more realistic, road profile description is proposed by Bogsjö where the road profile follows a non-stationary Laplace distribution. Another shortcoming of Rozyn's paper is that it only shows results for only one condition. For the simulation, the vehicle is driving 100 km/h and a measurement period of 1,000 seconds is used. Unknown is the influence of the velocity of the vehicle on the results. It is to be expected that the accuracy decreases for shorter measurement periods, but by how much is also unknown. In this thesis, Rozyn's algorithm is explained and implemented using a half car vehicle model. Rozyn's algorithm is validated using the ISO 8608 road profile description on similar conditions. The algorithm is then tested using the ISO 8608 road profile description where the velocity of the vehicle is varied between 30 and 100 km/h and the measurement periods between 30 and 120 seconds. This is done 100 times for each condition. This results in 100 estimates of the inertial parameters of each condition. From these results, the average and standard deviation between the estimates can be calculated. This is also done for the alternative Laplace road description. The resulting standard deviations are plotted in surface plots, as function of the varying velocity and measurement period. The results show that the standard deviation between the different estimated parameters when using the Laplace description for the road profile are up to 5 times higher compared to the ISO 8608 road profile description. The results also show that the performance of the algorithm is heavily dependent on the measurement time. A measurement time of at less than 60 seconds is not recommended, due to the large deviation in the estimated parameters. For the mass and centre of gravity position, the performance is independent of the velocity of the vehicle. However, the pitch moment of inertia shows a slight dependency on the velocity, with lower deviations between the different estimates for higher velocities. The algorithm can still be used on non-stationary road profiles. However, more and longer measurements are needed for the algorithm to return with an accurate estimation of the inertial parameters. Even then, some errors in the estimated parameters in the order of 10% are present.