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The on-vehicle automation system is primarily designed to replace the human driver during driving to enhance the performance and avoid possible fatalities. However, current implementations in automated vehicles (AVs) generally neglect that human imperfection and preference do not always lead to negative consequences, which prevents achieving optimized vehicle performance and maximized road safety. Human-like Decision-making and Control for Automated Driving takes a step forward to address breaking through the limitation of future automation applications, investigating in depth: Human driving feature modeling and analysis Personalized motion control for AVs Human-like decision making for AVs Click here to access the full SAE EDGETM Research Report portfolio.

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.

Energy management strategies greatly influence the power performance and fuel economy of series hybrid electric tracked bulldozers. In this paper, we present a procedure for the design of a power management strategy by defining a cost function, in this case, the minimization of the vehicle’s fuel consumption over a driving cycle. To explore the fuel-saving potential of a series hybrid electric tracked bulldozer, a dynamic programming (DP) algorithm is utilized to determine the optimal control actions for a series hybrid powertrain, and this can be the benchmark for the assessment of other control strategies. The results from comparing the DP strategy and the rule-based control strategy indicate that this procedure results in approximately a 7% improvement in fuel economy.

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.

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.

A novel type of regenerative braking system for electric vehicles is proposed in this paper. Four pressure-difference-limit valves, two relief valves and two brake pedal simulators, are added to the layout of a conventional four-channel hydraulic modulator. The cooperation of relief valves and hydraulic pumps provides a stabilized high-pressure source. Pressure-difference-limit valves ensure that the pressure in each wheel cylinder can be modulated separately at a high precision. Besides, the functions of anti-lock braking system and electronic stability program are integrated in this regenerative braking system. The models of regenerative braking controller and vehicle dynamics are built in MATLAB/Simulink. Hydraulic brake model is built in AMESim through a parameterized and modularized method. Meanwhile, the control strategy of hydraulic brake modulation and brake force distribution are designed.

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.

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.

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.

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.

As one of the key technologies of electrified vehicles, regenerative braking offers the capability of fuel saving by converting the kinetic energy of the moving vehicle into electric energy during deceleration. To coordinate the regenerative brake and friction brake, improving regeneration efficiency and guaranteeing brake performance and brake safety, development of special brake systems for electrified vehicles is needed. This paper presents a new type of electrically-controlled regenerative braking system (EABS) that has been developed for electrified passenger vehicles, which has the potential to be brought into production in China. By utilizing as much as possible mature components, integrating cooperative regeneration with ABS/TCS functions, EABS can achieve high regeneration efficiency and brake safety while providing system reliability, low development cost and development risk. This article describes the layout of the newly developed regenerative braking system.