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Optimum Vehicle Dynamics Control Based on Tire Driving and Braking

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Optimum Vehicle Dynamics Control Based on Tire Driving and Braking 23 Special Issue Modeling, Analysis and Control Methods for Improving Vehicle Dynamic Behavior Optimum Vehicle Dynamics Control Based on Tire Driving and Research Braking Forces Report Yoshikazu Hattori Abstract This paper discusses a method of controlling This report proposes a method of distributing the tire force exerted by each wheel of a vehicle the target force and moment of a vehicle to each as a means of ensuring steerability and stability. tire by considering variations in the tire force Conventional vehicle stability control systems caused by changes in the tire's vertical load, the generally rely on feedback of vehicle states such longitudinal slip, and so on. As a result, the as the side slip angle and yaw rate to enable proposed strategy achieves seamless behavior stabilization under a range of vehicle/road surface between the normal and the critical limit regions. combinations. On a low-friction road surface that And, we have confirmed that excellent levels of is incapable of applying sufficient force, steerability and stability can be achieved, relative however, it is unreasonable to expect a system to to conventional stability control systems, by provide sufficient control upon the occurrence of simulating a slalom maneuver. Also, this undesirable vehicle behavior. The tire force has a strategy enables effective vehicle control in the non-linear saturating characteristic, the value of face of unstable phenomena involving which varies with the vehicle state and road unbalanced lateral forces arising from changes in surface, making it difficult to determine the force the vehicle behavior, such as closing the throttle to be generated by each tire to ensure the desired during a turn maneuver. vehicle behavior. Keywords Vehicle dynamics control, Nonlinear optimum control, Tire model, Steerability, Stability R&D Review of Toyota CRDL Vol. 38 No. 4 24 1. Introduction Figure 1 illustrates the control provided by VDM. We refer to this illustration as the "Ball in a bowl." Since the 1980s, various chassis active control The ball corresponds to the vehicle state that is systems have been developed to ensure vehicle maintained within a conceptual "bowl" that stability. Direct-yaw moment control systems with corresponds to the control systems. Inside the bowl active braking, as typified by VSC (Vehicle Stability is the stable region, while outside it is the unstable Control) have realized good vehicle stability in the region. In conventional systems, the wall is 1-4) critical limit region. Those papers have mainly configured by several systems such as ABS, VSC, discussed control methods that feedback various and TCS (Traction Control System), all of which are aspects of the vehicle state, such as the side slip sheer just before facing an emergency situations. As angle and yaw velocity. a result, the vehicle motion can be stabilized, Some subsequent proposals have introduced although non-smooth motion may sometimes occur. vehicle and tire models to estimate the vehicle state VDM, on the other hand, enables smoother behavior, and calculate the yaw moment required to stabilize because it involves the conventional control systems 5-6) the vehicle. In earlier methods that handed over being restructured to form a continuous and smooth control of the vehicle immediately after detecting a "wall." To realize this level of control, the following vehicle skid, however, it was difficult to attain elements are important: smooth control. Therefore, a method of directly • Hierarchical algorithm involving the restructuring controlling the force and moment of the vehicle was of the conventional control strategy 7) proposed. Meanwhile, the tire force exhibits non- • Feedforward force and moment control for vehicle linear saturating characteristics according to the dynamics vehicle state and road surface conditions. • Nonlinear optimum distribution method that Additionally, these values change frequently. coordinates the operations of each actuator Therefore, it is not easy to determine the force that Each of the above is discussed in the following should be generated at each tire in order to obtain chapters. the target force and moment of the vehicle under any given driving situation. Hence, earlier systems used 3. Hierarchical algorithms for VDM rule-based methods to calculate the longitudinal Since vehicle control systems have continued to force at each wheel from the direct yaw moment. become more diversified, their algorithms need to be Against this background, next-generation vehicle able to easily manage the cooperative control of dynamics control should be able to provide seamless multiple systems such as the drive train, braking and vehicle steerability and stability at any time while steering. Accordingly, it is important to be able to driving, integrated control systems to use most of the ensure the compatibility of the algorithms with tire performance. different system configurations. To ensure the high First, we propose the new VDM (Vehicle level of performance, we require a model-based Dynamics Management) concept. Next, we suggest algorithm that uses feedforward control in addition three key technologies that are central to realizing to feedback control of the vehicle state. this concept. Finally, the performance of the proposed strategy is investigated by simulation. TCS VDM 2. Concept and key technologies of VDM VSC VSC The ultimate goal of vehicle dynamics control is to produce vehicles that anyone can drive "safely," "pleasantly," and "as one wishes." In realizing this, ABS we must embrace the key words of "seamlessly" and "anytime." To achieve this, we are proposing the VDM concept. Fig. 1 The evolution of control by VDM. R&D Review of Toyota CRDL Vol. 38 No. 4 25 An HVDM (Hierarchical Vehicle Dynamics individual tire forces, with the total becoming the Management) algorithm has been proposed to satisfy desired force and moment of the vehicle. the above requirements (Fig. 2). The HVDM [Wheel control] algorithm consists of small systems, each connected This layer calculates the target values for each hierarchically. actuator, such as the engine, braking, steering and so [Vehicle dynamics control] on. The target values are determined to generate the This layer calculates the desired longitudinal and desired tire forces. lateral forces, as well as the yaw moment of the [Actuator control] vehicle. The forces and moment are determined as Each actuator system is controlled. The braking the vehicle assumes the desired motion, taking the system, for example, uses actuated pressure valves driver's operations into account. to control the braking torque. [Force and moment distribution] The upper layer outputs the target values to the This layer determines the distribution of the lower layer, while the lower layer feeds back the results. The upper layer then recalculates the target value depending on the results. Information DriverInputs (Steer, Throttle,Brake) This both-way communication enables each layer Vehicle Dynamics Control to cooperate with the other and maintain greater Force &Moment of Vehicl e robustness corresponding to the characteristic Force & Moment Distribution change of the controlled system and environment. Tire Forces(Slip Ratios) 4. Adoption of force and moment control Wheel Control Figire 3 shows the proposed control flow. This Driving Torque Brake Pressure flow consists of two parts: One is feedforward Drive Train Control Brake Control control of the force and moment of the vehicle and (Target) the other is feedback control of the vehicle states. (Result) This type of system is generally called "Two- Degrees-of-Freedom Control." The main advantage Fig. 2 Hierarchical vehicle dynamics management of this system is that it enables the independent algorithm. design of controllability and stability.8) The feedforward control estimates the tire forces. FForce orce and MMoment oment VVehicle ehicle States Therefore, the part controlled as FeFeedforwarded forward FFeedback eedba ck the force and moment of the + - vehicle, as calculated by γ * β * , estimating the tire force, is RReference eferenc e Model * * * Feedback equal to the value obtained by Fx , Fy , Mz γ Controller , β the reference model. Feedback control stabilizes Driver + δ + Distribution the vehicle behavior as it δ - + ControllerC ontroller approaches the limit region Observe ˆ ˆ ˆ where the modeling error is ModelModel F , Fy , M VehiVehi cle x z large. Fxi , Fyi , M zi , By combining these two parts, δ vehicle behavior can be made smooth and the probability of approaching the critical limit Fig. 3 Vehicle dynamics control algorithm. can be reduced. R&D Review of Toyota CRDL Vol. 38 No. 4 26 proposed. It is based on the following tire model. 5. Nonlinear optimum distribution method 5. 1 Tire model The other core technology employed by VDM is a The characteristics that the tire force distribution force and moment distribution method that uses algorithm requires of the tire model are as follows. nonlinear optimization. As shown in Fig. 4, this • Saturation of tire force method distributes the target force and moment of • Dependency of driving and cornering stiffness the vehicle to the longitudinal and lateral forces of on vertical load each wheel. • Relationship between longitudinal and lateral It is well known that, when braking in a turn, the force (friction circle) distribution of the braking force in proportion to the • Fewer parameters for describing the model vertical load of each wheel causes the yaw moment The simple brush model described
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