Clemens Satzger

A model predictive control allocation approach to hybrid braking of electric vehicles

With the recent emergence of electric drivetrains, a faster and energy efficient braking actuator the electric motor has become available to complement the operation of the traditional friction brakes. The decision on how to split the braking torque among the friction brake and the electric motor is one of the main issues of such hybrid braking systems. With this challenge in mind, a new model predictive control allocation (MPCA) approach for hybrid braking is proposed. In comparison to state of the art torque blending solutions (daisy chain and dynamic control allocation) the MPCA offers faster transient response, without compromising the energy recuperation efficiency of the actuators. In addition, we also develop a linear wheel slip controller to regulate the braking force during emergency braking maneuvers. The tuning of this wheel slip controller is carried out using robust pole placement techniques, which ensures good operation in spite of uncertainties in the tire-road friction coefficient and the vertical load. Simulation results demonstrate the effectiveness of the proposed method.

Framework for the Evaluation of Wheel Torque Blending Algorithms

Electric vehicle power train concepts with wheel-hub or close-to-wheel propulsion open up a whole new area of vehicle control possibilities. The DLR robotic concept vehicle ROMO allows the evaluation of these possibilities using integrated chassis control. With its electric drive train it is possible to recuperate kinetic energy during braking process. Using only the electric motors for braking, an increased mass of electric drives & energy storage would be necessary in order to comply to legal passenger vehicle braking regulations. Therefore, the combination of friction based brake and electric motor brake can be advantageous. In this paper, object oriented models (Modelica) of a permanent magnet synchronous machine driven electro-hydraulic disc brake and an in-wheel direct driven traction motor are presented. Furthermore, two torque blending algorithms of an electro-hydraulic disc brake and an in-wheel permanent magnet synchronous machine are evaluated. One algorithm is based on a dynamic control allocation using real-time capable quadratic programming, the other is a feed forward control based on heuristic considerations. Finally, four comparison methods are presented and applied to evaluate the performance of the used torque blending.

Combined wheel-slip control and torque blending using MPC

This article is concerned with the design of braking control systems for electric vehicles endowed with redundant braking actuators, i.e., with friction brakes and wheel-individual electric motors. Facing the challenge to optimally split the braking torque between these two actuators, a unified model predictive control (MPC) algorithm is presented here. The proposed algorithm unifies the wheel slip controller and the torque blending functions into a single framework. The capability of handling energy performance metrics, actuator constraints and dynamics, represents the main advantages of this approach. Simulation studies demonstrate that, in comparison with state-of-art solutions, the proposed control strategy is able to improve the wheel slip and torque tracking by more than 20%, with minor penalization in the energy recuperation.

Predictive Brake Control for Electric Vehicles

This paper presents a predictive braking control algorithm for electric vehicles with redundant braking actuators, composed of friction brake actuator(s) and electric motor(s). The proposed algorithm is based on a model predictive control framework and is able to optimally tackle several control goals, such as maximization of energy recuperation and wheel slip regulation, while taking into account actuation dynamics and constraints. The braking control algorithm was simulated and experimentally validated on the ROMO research vehicle. The obtained results demonstrate that in comparison with state-of-the-art control techniques, the proposed model predictive control approach is able to reduce the torque tracking error up to 60%, and improve the deceleration during emergency braking up to 10%.

Fault-tolerant control of an electrohydraulic brake using virtual pressure sensor

An approach for fault tolerant control of an electrohydraulic brake (EHB) in case of a pressure sensor failure is presented. Automotive Brake-by-Wire actuators are safety critical components, and an EHB under closed-loop pressure control is critically affected by faults in the pressure sensor. Timely fault detection and reconfiguration to use a brake pressure estimate based on motor position enhances the reliability of the system. Since the relationship between position and pressure can vary over a systems lifetime due to wear and changes in brake system characteristics, it is necessary to adapt this relationship online using operating data. This paper presents the means to perform this update using a least squares estimation routine, adapted to account for persistence of excitation and data storage limitations. Model-based fault detection functions are also presented. The proposed fault-tolerant control approach is implemented and validated on an EHB test bench with promising results.

Design and validation of an MPC-based torque blending and wheel slip control strategy

This article presents a braking control algorithm for electric vehicles endowed with redundant actuators, i.e. friction brakes and wheel-individual electric motors. This algorithm relies on a model predictive control framework and is able to optimally split the wheel braking torque among the redundant actuators, while providing anti-lock braking features (i.e. wheel slip regulation). It will be shown that, the integration of these two control functions together with energy metrics, actuator constraints and dynamics improves the control performance compared to state-of-art control structures. Additionally, experimental measurements recorded with our prototype vehicle demonstrate a precise wheel slip regulation and high energy efficiency of the proposed braking control methodology.