Dynamic braking

About: Dynamic braking is a research topic. Over the lifetime, 3472 publications have been published within this topic receiving 34897 citations. The topic is also known as: Rheostatic brake.

Electric vehicle regenerative antiskid braking and traction control system

Abstract: An antiskid braking and traction control system for an electric or hybrid vehicle having a regenerative braking system operatively connected to an electric traction motor, and a separate hydraulic braking system includes one or more sensors for monitoring present vehicle parameters and a processor, responsive to the sensors, for calculating vehicle parameters defining the vehicle behavior not directly measurable by the sensors and determining if regenerative antiskid braking control, requiring hydrualic braking control, or requiring traction control are required. The processor then employs a control strategy based on the determined vehicle state and provides command signals to a motor controller to control the operation of the electric traction motor and to a brake controller to control fluid pressure applied at each vehicle wheel to provide the appropriate regenerative antiskid braking control, hydraulic braking control, and traction control.

Vehicle speed control with continuously variable braking torque

Abstract: A system and method for reducing speed of a vehicle to maintain a target vehicle speed include determining an actual vehicle speed, comparing the target vehicle speed to the actual vehicle speed to generate a speed error, determining a continuously variable braking torque as a function of the speed error when the actual vehicle speed exceeds the target vehicle speed, and applying the continuously variable braking torque to at least one wheel of the vehicle to reduce the speed error toward zero and control the speed of the vehicle. The present invention is applicable to vehicles powered by an internal combustion engine, electric vehicles, fuel cell vehicles, and hybrid vehicles. The continuously variable braking torque may be applied using regenerative braking to improve fuel efficiency. Friction brakes may also be utilized either alone, or in combination with regenerative braking, for vehicles capable of brake-by-wire control strategies.

Modeling and Integration of Electric Vehicle Regenerative and Friction Braking for Motor/Dynamometer Test Bench Emulation

Abstract: This paper provides a new approach for emulating electric vehicle (EV) braking performance on a motor/dynamometer test bench. The brake force distribution between regenerative braking and friction braking of both the front and rear axles are discussed in detail. A brake controller is designed, which represents a very close model of an actual EV braking system and takes into account both regenerative and friction braking limitations. The proposed brake controller is then integrated into the controller of an EV hardware-in-the-loop (HIL) test bench, and its performance is validated in real-time. The effect of adding the brake model is further investigated by comparing the experimental HIL energy consumption results with those obtained from ADvanced VehIcle SimulatOR (ADVISOR).

Model predictive regenerative braking control for lightweight electric vehicles with in-wheel motors:

Abstract: This paper presents a nonlinear model predictive controller for regenerative braking control of lightweight electric vehicles equipped with in-wheel motors. In-wheel-motors-driven electric vehicles...

Electrical vehicle modeling

Abstract: A fuzzy logic model for modeling regenerative braking systems is presented.Model output is the ratio of regenerative braking force to the total braking force.Model can be adapted to be used in traffic simulators like the SUMO simulator.Real data was gathered from short and long-distance field tests with a Nissan LEAF.Results were compared with real-world data obtained with a Nissan LEAF in road tests. This paper presents a fuzzy logic model of regenerative braking (FLmRB) for modeling EVs' regenerative braking systems (RBSs). The model has the vehicle's acceleration and jerk, and the road inclination as input variables, and the output of the FLmRB is the regeneration factor, i.e. the ratio of regenerative braking force to the total braking force. The regeneration factor expresses the percentage of energy recovered to the battery from braking. The purpose of the FLmRB development is to create realistic EV models using as least as possible manufacturers intellectual property data, and avoiding the use of EV on-board sensors. To tune the model, real data was gathered from short and long-distance field tests with a Nissan LEAF and compared with two types of simulations, one using the proposed FLmRB, and the other considering that all the braking force/energy is converted to electric current and returned back to charge the battery (100% regeneration). The results show that the FLmRB can successfully infer the regenerative braking factor from the measured EV acceleration and jerk, and road inclination, without any knowledge about the EV brake control strategy.