Abstract
The principles of operation and the architecture for perspective automotive systems of active safety (SAS), which are concerned with the intelligent approaches in automotive engineering, is the subject of the article. The main features of intelligent SAS are the forecasting of critical situations, the self-learning algorithms and the parallel information structure. On this basis, the following problems for intelligent SAS should be decided:
Definition of estimation criteria for critical situations at automobile movement,
Creation of control philosophy;
Definition of the approaches to information structure generation.
The active safety as a property of an automobile is connected with concept of critical situation. In this situation both a single wheel and a vehicle can move near the boundary areas on stability, handling, traction or brake efficiency. The given areas result from road conditions and are subjected to many factors.
The two-level representation of the influential active safety factors is offered to development of objective estimated criteria.
On a micro-level the critical situations are stipulated by wheel-road-interaction, on macrolevel by vehicle behaviour. Moreover, the factors of each level are subdivided into external and internal factors. On this prerequisite the concept of active safety coefficients is introduced. The micro-level coefficient can be evaluated by a ratio of actual and potential forces in the wheel-road contact. The macro-level coefficient depends on a number of vehicle dynamic characteristics. The given parameters can be evaluated on the basis of energy distribution at vehicle movement. Both coefficients are related by the general active safety coefficient, which allows estimating the criticality of vehicle manoeuvre at any time point.
The necessity to forecast a critical situation has motivated development of intelligent, pre-extreme control philosophy for intelligent SAS. Typically the modern SAS take advantage of the discrete control through reference values of the wheel slip and/or of the velocity derivative. Pre-extreme control is associated with quasi-continuous regulation, which is founded on the analysis of tire grip µ - wheel sliding s - dependencies. The estimation of energy processes at wheel rolling has allowed to set up a hypothesis about regularity in pre-extreme area of µ-s-curves. On this basis the prognostic algorithms for SAS can be designed.
For intelligent control philosophy and self-learning algorithms the parallel information structure with several control parameters (e.g. wheel slip, forces in the wheel-road contact, turning moment of inertia of vehicle etc.) should be implemented into SAS. It has following features. Firstly, the information provided by sensors is handled so that to receive not any current parameter point, but its time functions. It allows tracing the tendencies to transition of control object in the critical area of movement. Secondly, the system places the priorities for information channels depending on an estimation of a current control situation. At emergency or overload of information channels the resources of SAS are reallocated.
Besides, the system is capable to retarget the units of circuit "Information-Processing-Control" depending on gained operational experience for the specified object.
The research result is the originated strategic concept for the intelligent systems, which are closely integrated with the driver and current road situation and allow to realise the automotive active safety at a new quality level.