Jens Kalkkuhl

Gain-scheduled wheel slip control in automotive brake systems

A wheel slip controller is developed and experimentally tested in a car equipped with electromechanical brake actuators and a brake-by-wire system. A gain scheduling approach is taken, where the vehicle speed is viewed as a slowly time-varying parameter and the model is linearized about the nominal wheel slip. Gain matrices for the different operating conditions are designed using an LQR approach. The stability and robustness of the controller are studied via Lyapunov theory, frequency analysis, and experiments using a test vehicle.

Vehicle velocity estimation using nonlinear observers

Nonlinear observers for estimation of lateral and longitudinal velocity of automotive vehicles are proposed. The observers are based on a sensor suite that is standard in many new cars, consisting of acceleration and yaw rate measurements in addition to wheel speed and steering angle measurements. Two approaches are considered: first, a modular approach where the estimated longitudinal velocity is used as input to the observer for lateral velocity, and second, a combined approach where all states are estimated in the same observer. Both approaches use a tire-road friction model, which is assumed to be known. It is also assumed that the road is flat. Stability of the observers is proven in the form of input-to-state stability of the observer error dynamics, under a structural assumption on the friction model. The assumption on the friction model is discussed in detail, and the observers are validated on experimental data from cars.

Nonlinear vehicle side-slip estimation with friction adaptation

A nonlinear observer for estimation of the longitudinal velocity, lateral velocity, and yaw rate of a vehicle, designed for the purpose of vehicle side-slip estimation, is modified and extended in order to work for different road surface conditions. The observer relies on a road-tire friction model and is therefore sensitive to changes in the adhesion characteristics of the road surface. The friction model is parametrized with a single friction parameter, and an update law is designed. The adaptive observer is proven to be uniformly globally asymptotically stable and uniformly locally exponentially stable under a persistency-of-excitation condition and a set of technical assumptions, using results related to Matrosovs theorem. The observer is tested on recorded data from two test vehicles and shows good results on a range of road surfaces.

Improved transient performance of nonlinear adaptive backstepping using estimator resetting based on multiple models

It is proved that the the transient performance of nonlinear adaptive backstepping can be improved by re-setting the parameter estimator, without loss of stability. The estimator re-setting algorithm is based on multiple-model adaptive control, where a number of models with fixed parameter vectors are monitored online in order to detect a parameter vector that gives a negative jump in the control Lyapunov function when replacing the estimate provided by the standard adaptation law. An application to wheel slip control is studied.

Vehicle sideslip estimation

The objective of this article is to develop a vehicle sideslip observer that takes the nonlinearities of the system into account, both in the theoretical analysis and the design. The design goals include reduction of the computational complexity compared to the EKF, to make the observer suitable for implementation in the embedded hardware, and a reduction in the number of tuning parameters compared to the EKF. Design is based on a standard sensor configuration, and is subjected to the extensive testing in the realist conditions.

Hybrid control strategies in ABS

The ABS control problem is described, with a discussion on relevant hybrid control aspects. Next, we comment on conventional ABS design methods and present some new ideas and results on model-based ABS control design that relies on elements of hybrid control.

Nonlinear Observer for Vehicle Velocity with Friction and Road Bank Angle Adaptation - Validation and Comparison with an Extended Kalman Filter

Many active safety systems in automotive vehicles, for instance yaw stability systems such as ESC/ESP, depend on information about vehicle velocity, in particular lateral velocity or side-slip angle, to be able to function properly. However, the vehicle velocity is rarely measured directly due to issues of cost and reliability, and must therefore in general be inferred from other measurements, such as wheel speed, steering angle, yaw rate, and acceleration measurements.

Speed control design for an experimental vehicle using a generalized gain scheduling approach

Describes the design and experimental evaluation of a nonlinear automotive speed control system. The approach implemented is based on interpolation of multiple linear controllers designed using multiple local linear models. This is a generalized form of gain scheduling since the models and controllers take explicit account of both stationary and nonstationary (off-equilibrium) operating points. The paper focuses on engineering aspects and experimental evaluation in a test vehicle. The nonlinear controller is tested on a range of speed-profile tracking tasks, and in a disturbance rejection task (the vehicle is driven up a 10% slope). For comparison, linear controllers are implemented. The proposed nonlinear control approach gives excellent performance over the complete operational range. The nonlinear controller can directly account for the strong plant nonlinearities and the engineering constraints.

Constructive empirical modelling of longitudinal vehicle dynamics using local model networks

Abstract In this paper a number of empirically derived parametric models of longitudinal vehicle dynamics are compared. The vehicle concerned is a fully instrumented Mercedes-Benz commercial lorry. The main focus is on a class of models known as local model networks. In this structure, a number of simple local linear models are combined (‘interpolated’) by ‘scheduling’ on a number of physical variables which are known to, or can be found to, capture the system non-linearities. Following extensive experimentation involving the use of constructive search for operating regime decomposition, it is concluded that scheduling on gear and throttle angle leads to the best overall model. Local 1st-order linear ARX models are found to be sufficient. For comparison, a non-linear model of Hammerstein type and a multi-layer perceptron neural-network are also identified.

Vehicle Velocity Estimation using Modular Nonlinear Observers

Nonlinear observers for estimation of lateral and longitudinal velocity of automotive vehicles are proposed, based on acceleration and yaw rate measurements in addition to wheel speed and steering angle. The observer for lateral velocity uses a tyre-road friction model. Exponential stability of the observers are shown. A structural assumption on the friction model is discussed. The observer structure is validated using experimental data from cars.