Leo Laine

Wheel force distribution for improved handling in a hybrid electric vehicle using nonlinear control

In this paper a vehicle motion controller is presented. The idea is to use generalized forces acting on the center of gravity of the vehicle and then use a control allocation-like method to distribute the generalized forces to wheel forces. The controller is designed based on feedback linearization of a simple vehicle model. The performance of the controller is evaluated by simulations on a more complex vehicle model. The proposed controller can handle the new flexibility introduced by new powertrain configurations, this is shown by using the same controller on two different vehicle configurations.

Real-time performance of control allocation for actuator coordination in heavy vehicles

This paper shows how real-time optimisation for actuator coordination, known as control allocation, can be a viable choice for heavy vehicle motion control systems. For this purpose, a basic stability control system implementing the method is presented. The real-time performance of two different control allocation solvers is evaluated and the use of dynamic weighting is analysed. Results show that sufficient vehicle stability can be achieved when using control allocation for actuator coordination in heavy vehicle stability control. Furthermore, real-time simulations indicate that the optimisation can be performed with the computational capacity of todays standard electronic control units.

Coordination of Vehicle Motion and Energy Management Control Systems for Wheel Motor Driven Vehicles

This paper shows how smooth coordination of vehicle motion controller and energy management can be achieved when control allocation is used for over-actuated ground vehicles. The ground vehicle studied here is equipped with four electric wheel motors, four disc brakes, and front and rear steering. This gives a total of ten input signals to control the desired vehicle motion in longitudinal-, lateral-, and yaw-direction. Simulations show that the desired input signals from energy management and steering can be fulfilled, but when needed the actual input signals for the motion actuators are smoothly diverted from the desired input signals due to vehicle stability reasons and/or saturation of the actuators.

Proposal for using Sine With Dwell on low friction for the evaluation of yaw stability for heavy vehicle combinations

This paper proposes how the test case Sine With Dwell could be modified for the evaluation of yaw stability of heavy vehicles. The test case was originally proposed by the National Highway Traffic Safety Administration (NHTSA) for evaluation of Electronic Stability Programs (ESP) performance during an oversteer situation on high friction. The modified test case presented here accounts for the heavy vehicle dynamics through three main modifications of the original test case. Firstly, to avoid rollover, the test case is performed on low friction. Secondly, to avoid excess understeer behaviour, the steering input frequency is lowered compared to the original test. Thirdly, to account for response times, the responsiveness and stability criteria are modified. These modifications are derived from hardware in the loop simulations and field tests for different tractor/truck and trailer combinations. By using the modified responsiveness and stability criteria it was shown that the tested ESP system could be objectively evaluated. A clear improvement on vehicle stability was seen in the results when ESP was used.

Control Allocation based Electronic Stability Control System for a Conventional Road Vehicle

This paper shows how control allocation with an optimization formulation can be used as an on-line electronic stability control system for a conventional road vehicle. Control allocation is used in systems with more actuators than the degrees of freedom controlled, which are also known as over-actuated systems. Here it is assumed that the steering is solely managed by the driver. The control allocator uses the combustion engine and the four mechanical disc brakes to compensate any understeering or oversteering behaviour. Simulations showed that the suggested control system passed the proposed test procedure for Electronic Stability Control systems, sine with dwell, suggested by the National Highway Traffic Safety Administration (NHTSA).

Coordination of actuators for an A-double heavy vehicle combination using control allocation

This paper shows how actuator coordination, based on control allocation, can be used in the motion control system for long articulated heavy vehicles. Usage of a control allocation structure is one way to handle an over-actuated system, which is a system where there are more motion actuators than controlled motions. The A-double combination is in focus for the control allocation design, which is based on vehicle modelling using the Lagrange formulation. The control structure is tested in a simulation environment and evaluated by two test scenarios. For the selected configuration with 31 actuators, the control allocation method coordinates the desired motion for both large and small steer and articulation angles. The proposed control structure is shown to be convenient when the vehicle configuration, for example the number of actuators in the combination, is changed.

Inverse model control including actuator dynamics for active dolly steering in high capacity transport vehicle

This paper describes an advance controller designed using the nonlinear inversion technique of a Modelica® based simulation tool, such as Dymola®, for active dolly steering of a high capacity transport vehicle. Actuator dynamics is included in the inverse model controller. Therefore, it can automatically generate required steering angle request for the dolly axles of the vehicle combination. The resultant controller is transfered as a functional mock-up unit (FMU) to Simulink® environment where the actual simulations are conducted. The controller is simulated against a high-fidelity vehicle model of an A-double combination from Virtual Truck Models (VTM) library - developed by Volvo Group Trucks Technology. Effects of variations of the actual actuator dynamics, with respect to the modeled dynamics in the inverse model controller, on overall vehicle performance are investigated.

Driver Model Based Automated Driving of Long Vehicle Combinations in Emulated Highway Traffic

This paper proposes a framework for automated highway driving of an A-double long vehicle combination. The included driving manoeuvres are maintain lane, lane change to right and left, abort lane change to right and left, and emergency brake. A combined longitudinal and lateral driver model is used for the generation of longitudinal acceleration and steering requests. The behaviour of the driver model, both regarding heuristics and safety thresholds, is inspired by human cognition and optical flow theory. Traffic situation predictions of feasible lane changes are calculated using the driver model in combination with prediction models of the subject and surrounding vehicles. The traffic situation predictions are used for the evaluation of constraints related to vehicle dynamics, road boundaries and distance to surrounding objects. When the framework is started, the subject vehicle is initiated in the maintain lane state respecting the road speed limit and the distance to surrounding objects. A lane change manoeuvre is performed on request from the driver when the corresponding traffic situation prediction and control request become feasible. The framework has been implemented in a simulation environment including a high-fidelity vehicle plant model and models of surrounding vehicles. Simulations show that the framework gives anticipated results when initial conditions are varied. Results are shown for maintain lane and lane change manoeuvres at constant longitudinal velocity, varying from 20-80 km/h and lane changes combined with retardation including leading vehicle braking from different initial velocities ranging from 30-80 km/h.

Combining Coordination of Motion Actuators with Driver Steering Interaction

Objective: A new method is suggested for coordination of vehicle motion actuators; where driver feedback and capabilities become natural elements in the prioritization. Methods: The method is using a weighted least squares control allocation formulation, where driver characteristics can be added as virtual force constraints. The approach is in particular suitable for heavy commercial vehicles that in general are over actuated. The method is applied, in a specific use case, by running a simulation of a truck applying automatic braking on a split friction surface. Here the required driver steering angle, to maintain the intended direction, is limited by a constant threshold. This constant is automatically accounted for when balancing actuator usage in the method. Results: Simulation results show that the actual required driver steering angle can be expected to match the set constant well. Furthermore, the stopping distance is very much affected by this set capability of the driver to handle the lateral disturbance, as expected. Conclusion: In general the capability of the driver to handle disturbances should be estimated in real-time, considering driver mental state. By using the method it will then be possible to estimate e.g. stopping distance implied from this. The setup has the potential of even shortening the stopping distance, when the driver is estimated as active, this compared to currently available systems. The approach is feasible for real-time applications and requires only measurable vehicle quantities for parameterization. Examples of other suitable applications in scope of the method would be electronic stability control, lateral stability control at launch and optimal cornering arbitration.

A Driver Model Using Optic Information for Longitudinal and Lateral Control of a Long Vehicle Combination

High driver acceptance is believed to be an important aspect when introducing automated driving functionalities for prospective long vehicle combinations. The main hypothesis of this paper is that high driver acceptance can be realized by utilizing driver models inspired by human cognition as an integrated part of such functions. It is envisioned that the human driver will more easily understand, and trust, a system that behaves in a human-like manner. In the study of a combined retardation and lane-change scenario, a driver model based on optic information was used, together with a single track vehicle model, to control the steering and retardation of a simulated vehicle. The parameters of the driver models lateral behavior were estimated using driving data measured from an A-double combination during actual lane-changes. Numerical simulations showed that the driver model was able to generate safe and conservative deceleration and steering for the studied scenario. In future work for automated functionalities, the combined driver and vehicle model could be used when evaluating different tentative plans for lane changes, in real time.