On torque vectoring to improve steering predictability while minimising power loss in heavy electric vehicles using model predictive control
Publicerad
Författare
Typ
Examensarbete för masterexamen
Master's Thesis
Master's Thesis
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
The vehicle industry is moving towards electrical propulsion, and thereby improving
the capabilities of the powertrain designs. Examples are the ability to produce both
positive and negative torque, and the ability to have individually controlled wheels.
These abilities also add redundancy to the powertrain system while allowing its primary objective of achieving the desired vehicle motion to be met. It may then fulfil
secondary objectives, such as minimising power losses or tyre wear. With multiple
motors, it is possible to micromanage the dynamics of the vehicle by varying the
torque distribution on different wheels. This is called torque vectoring and includes
the act of varying torque both in the longitudinal and lateral direction. This thesis
analyses the impact of torque vectoring on a 4x4 heavy electric vehicle.
The torque vectoring controller acts as a global force request generator, taking in
a yaw rate reference together with either an acceleration request in form of pedal
positions from the driver or a velocity request in an autonomous driving algorithm.
The outputs of the controller are the requested global forces, which are then distributed to the actuators using control allocation, while optimising for power loss
minimisation. A Model Predictive Controller (MPC), with a prediction horizon of
1 second, was chosen as the motion coordinator, as it is able to account for actuator
and friction limitations and ensure that the requested forces to the control allocation are feasible. The target for the lateral control, in the MPC, was chosen as the
vehicle’s steady state yaw rate response, as it reduces the amount of compensation
from the driver during acceleration or braking.
Results show that the lateral control from the MPC is able to reduce the braking
distance in a curve, as well as reduce the steering wheel angle compensation from the
driver when hard braking with 20-30 degrees. In addition, it is able to minimise the
change in vehicle behaviour caused by changing distribution of propulsion between
front and rear motors. In a simulation on road data from Hällered to Alingsås (distance of 2.8 km), the controller uses approximately 1.3% more power than a vehicle
with no lateral control. An alternate controller style was developed to only interfere
when the vehicle diverged from the expected behaviour. This controller managed to
decrease the excess power consumption to 0.1% more than no lateral control.
Beskrivning
Ämne/nyckelord
Torque Vectoring, MPC, Power Loss, Steering Feel, Predictable, Heavy Vehicles