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Technical Paper

Design Optimization of the Transmission System for Electric Vehicles Considering the Dynamic Efficiency of the Regenerative Brake

In this paper, gear ratios of a two-speed transmission system are optimized for an electric passenger car. Quasi static system models, including the vehicle model, the motor, the battery, the transmission system, and drive cycles are established in MATLAB/Simulink at first. Specifically, since the regenerative braking capability of the motor is affected by the SoC of battery and motors torque limitation in real time, the dynamical variation of the regenerative brake efficiency is considered in this study. To obtain the optimal gear ratios, iterations are carried out through Nelder-Mead algorithm under constraints in MATLAB/Simulink. During the optimization process, the motor efficiency is observed along with the drive cycle, and the gear shift strategy is determined based on the vehicle velocity and acceleration demand. Simulation results show that the electric motor works in a relative high efficiency range during the whole drive cycle.
Technical Paper

Regenerative Brake-by-Wire System Development and Hardware-In-Loop Test for Autonomous Electrified Vehicle

As the essential of future driver assistance system, brake-by-wire system is capable of performing autonomous intervention to enhance vehicle safety significantly. Regenerative braking is the most effective technology of improving energy consumption of electrified vehicle. A novel brake-by-wire system scheme with integrated functions of active braking and regenerative braking, is proposed in this paper. Four pressure-difference-limit valves are added to conventional four-channel brake structure to fulfill more precise pressure modulation. Four independent isolating valves are adopted to cut off connections between brake pedal and wheel cylinders. Two stroke simulators are equipped to imitate conventional brake pedal feel. The operation principles of newly developed system are analyzed minutely according to different working modes. High fidelity models of subsystems are built in commercial software MATLAB and AMESim respectively.
Technical Paper

Recognizing Driver Braking Intention with Vehicle Data Using Unsupervised Learning Methods

Recently, the development of braking assistance system has largely benefit the safety of both driver and pedestrians. A robust prediction and detection of driver braking intention will enable driving assistance system response to traffic situation correctly and improve the driving experience of intelligent vehicles. In this paper, two types unsupervised clustering methods are used to build a driver braking intention predictor. Unsupervised machine learning algorithms has been widely used in clustering and pattern mining in previous researches. The proposed unsupervised learning algorithms can accurately recognize the braking maneuver based on vehicle data captured with CAN bus. The braking maneuver along with other driving maneuvers such as normal driving will be clustered and the results from different algorithms which are K-means and Gaussian mixture model (GMM) will be compared.
Journal Article

Cyber-Physical System Based Optimization Framework for Intelligent Powertrain Control

The interactions between automatic controls, physics, and driver is an important step towards highly automated driving. This study investigates the dynamical interactions between human-selected driving modes, vehicle controller and physical plant parameters, to determine how to optimally adapt powertrain control to different human-like driving requirements. A cyber-physical system (CPS) based framework is proposed for co-design optimization of the physical plant parameters and controller variables for an electric powertrain, in view of vehicle’s dynamic performance, ride comfort, and energy efficiency under different driving modes. System structure, performance requirements and constraints, optimization goals and methodology are investigated. Intelligent powertrain control algorithms are synthesized for three driving modes, namely sport, eco, and normal modes, with appropriate protocol selections. The performance exploration methodology is presented.
Journal Article

Comprehensive Optimization of Dynamics Performance and Energy Consumption for an Electric Vehicle via Coordinated Control of SBW and FIWMA

This paper presents a coordinated controller for comprehensive optimization of vehicle dynamics performance and energy consumption for a full drive-by-wire electric vehicle, which is driven by a four in-wheel motor actuated (FIWMA) system and steered by a steer-by-wire (SBW) system. In order to coordinate the FIWMA and SBW systems, the mechanisms influencing the vehicle dynamics control performance and the energy consumption of the two systems are first derived. Second, the controllers for each subsystem are developed. For the SBW system, a triple-step control technique is implemented to decouple the yaw rate and sideslip angle controls. The FIWMA system controller is designed with a hierarchical control scheme, which is able not only to satisfy the yaw rate and sideslip angle tracking demands, but also to deal with actuation redundancy and constraints.
Journal Article

Synthesis of a Hybrid-Observer-Based Active Controller for Compensating Powetrain Backlash Nonlinearity of an Electric Vehicle during Regenerative Braking

Regenerative braking provided by an electric powertrain is far different from conventional friction braking with respect to the system dynamics. During regenerative decelerations, the nonlinear powertrain backlash would excite driveline oscillations, deteriorating vehicle drivability and blended brake performance. Therefore, backlash compensation is worthwhile researching for an advanced powertrain control of electrified vehicles during regenerative deceleration. In this study, a nonlinear powertrain of an electric passenger car equipped with a central motor is modeled using hybrid system approach. The effect of powertrain backlash gap on vehicle drivability during regenerative deceleration is analyzed. To further improve an electric vehicle's drivability and blended braking performance, an active control algorithm with a hierarchical architecture is studied for powertrain backlash compensation.
Technical Paper

Robust Control of Anti-Lock Brake System for an Electric Vehicle Equipped with an Axle Motor

As the main power source of the electric vehicle, the electric motor has outstanding characteristics including rapid response, accurate control and four-quadrant operation. Being introduced into the dynamic chassis control of electrified vehicles, the electric motor torque can be used not only for driving and regenerative braking during normal operating conditions, but also offers a great potential to improve the dynamic control performance of the anti-lock braking under emergency deceleration situations. This paper presents a robust control algorithm for anti-lock braking of a front-wheel-drive electric vehicle equipped with an axle motor. The hydraulic and regenerative braking system of the electric vehicle is modeled as a LPV (linear parameter varying) system. The nonlinearities of the control system are considered as uncertain parameters of a linear fractional transformation.
Technical Paper

Regenerative Braking Control Algorithm for an Electrified Vehicle Equipped with a By-Wire Brake System

Regenerative braking, which can effectively improve vehicle's fuel economy by recuperating the kinetic energy during deceleration processes, has been applied in various types of electrified vehicle as one of its key technologies. To achieve high regeneration efficiency and also guarantee vehicle's brake safety, the regenerative brake should be coordinated with the mechanical brake. Therefore, the regenerative braking control performance can be significantly affected by the structure of mechanical braking system and the brake blending control strategy. By-wire brake system, which mechanically decouples the brake pedal from the hydraulic brake circuits, can make the braking force modulation more flexible. Moreover, its inherent characteristic of ‘pedal-decouple’ makes it well suited for the implementation in the cooperative regenerative braking control of electrified vehicles.