Mathematical modeling and simulation of an electric vehicle

As electric vehicles become promising alternatives for sustainable and cleaner energy emissions in transportation, the modeling and simulation of electric vehicles has attracted increasing attention from researchers. This paper presents a simulation model of a full electric vehicle on the Matlab-Simulink platform to examine power flow during motoring and regeneration. The drive train components consist of a motor, a battery, a motor controller and a battery controller; modeled according to their mathematical equations. All simulation results are plotted and discussed. The torque and speed conditions during motoring and regeneration were used to determine the energy flow, and performance of the drive. This study forms the foundation for further research and development

Analysis Tool for Fuel Cell Vehicle Hardware and Software (Controls) with an Application to Fuel Economy Comparisons of Alternative System Designs

In the area of analysis, a modeling tool for fuel cell vehicles needs to address the transient dynamic interaction between the electric drive train and the fuel cell system. Especially for vehicles lacking an instantaneously responding on-board fuel processor, this interaction is very different from the interaction between a battery (as power source) and an electric drive train in an electric vehicle design. Non-transient modeling leads to inaccurate predictions of vehicle performance and fuel consumption. Applied in the area of development, the existing programs do not support the employment of newer techniques, such as rapid prototyping. This is because the program structure merges control algorithms and component models, or different control algorithms are lumped together in one single control block and not assigned to individual components as they are in real vehicles. In both cases, the transfer of control algorithms from the model into existing hardware is not possible. The simulation program developed in this dissertation recognizes the dynamic interaction between fuel cell system, drive train and optional additional energy storage. It provides models for four different fuel cell vehicle topologies: 1) A load following fuel cell vehicle; 2) A battery hybrid fuel cell vehicle; 3) An ultra-capacitor hybrid fuel cell vehicle in which the ultra-capacitor unit is coupled via a dc-dc converter to the stack; 4) An ultra-capacitor hybrid fuel cell vehicle with direct coupling between fuel cell stack and ultra-capacitor. The structure of the model is a causal and forward-looking. The model separates the modeling of control algorithms from the component models. The setup is strictly modular and encourages the use of rapid prototyping techniques in the development process. The first half of the dissertation explains the model setup. In the second half of the dissertation, the simulation of different hybrid vehicle designs illustrates the capabilities of the model

Fuel cell-hybrid electric vehicle power train system design and control

Recently, due to elevated oil prices and the need for low emissions, the automotive industry has been clamoring for cleaner, more energy-efficient vehicles. Fuel cell-hybrid electric vehicles (FC-HEV) are considered to be one of the most promising alternatives, because of their evident advantages of much higher fuel efficiency and lower (or zero) emissions, without any significant restriction on driving range and vehicle performance. However, a number of severe obstacles need to be overcome to attain widespread commercialization of FC-HEVs. The most critical aspects of fuel cell vehicle research include the development of optimal power management strategies and design of efficient power train architectures. Firstly, this thesis attempts to solve the critical power management problem through the optimal design, modeling, and testing of innovative power control strategies. Thereafter, the advantages and limitations of the proposed strategies are compared and analyzed in depth. Secondly, the thesis also discusses the selection of suitable power train configurations, followed by the power electronic system design, based on hybridization degree and component characteristics. The circuit-level simulation results indicate that the power electronic control system can precisely implement the overall power control strategy, starting from the high-level supervisory control system. Finally, an attractive short-term future option, in the form of a plug-in fuel cell hybrid vehicle (FC-PHEV), is introduced. A suitable power management strategy is designed for the proposed FC-PHEV, with detailed discussions on critical performance as well as practical issues

COMPREHENSIVE THERMAL MODELING OF POWER SPLIT HYBRID POWER-TRAIN AND ELECTRONICS

Hybrid electric vehicle (HEV) uses both internal combustion engine (ICE) with an electric system. The combination of the electric power train with the ICE is intended to achieve both better fuel economies than the conventional vehicles and better performance. Several types of HEV exist with different layouts. Recent HEVs\u27 make use of regenerative braking, which converts the vehicles\u27 kinetic energy into electric energy instead of wasting it as heat as conventional brakes do. A hybrid-electric is more fuel efficient than ICE and has less environmental impact. The new HEV with its new Key Characteristics and Configurations (i.e. Mechanical complexity, Multiple driving modes, Multiple prime movers, ... etc) inflict an interference with the existed thermal management system of the conventional vehicles, which leads to a new thermal management issues that should be addressed to enhance the performance of such systems. There is no complete knowledge in the open literature about the thermal management issues of HEV yet. This dissertation introduces Comprehensive Thermal Modeling of Hybrid Vehicular systems to assist monitoring the added-on of hybrid modules into the vehicle thermal management system. The model proposes a combined experimental and finite differencing nodal net work simulation modeling approach; using Thermography detectors calibrated for emissivity to capture 2-D spatial and transient temperature measurements. The Thermographic detectors were deployed through dual band thermography to neutralize the emissivity and to provide different dynamic ranges to iii achieve accurate temperature measurements. A thermocouples network was installed to provide a reference signal. A new comprehensive 3-D thermal model was developed by generating 3-D surface description for a complete hybrid electric vehicle from 3-D scans of an actual vehicle to guarantee the quality of the surface geometry, and break down the surfaces of the model into finite elements to improve the accuracy for better thermal analysis. The boundary conditions from a vehicle under different driving modes and load scenarios were deployed into the finite differencing simulation which was performed using finite differencing code capable of solving a sophisticated thermal/fluid systems with minimal user interaction (RadTherm) to provide a 3-D Thermal predictions and an Image Viewer (wireframe and animated thermal display). The 3-D model assisted monitoring the adding of Hybrid modules into the vehicle thermal management system and was used to analyze packaging considerations and integrating different modules for Hybrid Vehicles. In addition to the design of alternative materials for hybrid modules and Battery Packs for better thermal management; the model assisted studying the influence of applying different cooling methodologies and evaluate its effect on the thermal performance of the HEVs\u27 power trains. A spatial and a transient temperature profiles obtained from the simulation for different components were compared with experimental results in order to validate the complete thermal model

Mathematical Modeling and Simulation of an Electric Vehicle

As electric vehicles become promising alternatives for sustainable and cleaner energy emissions in transportation, the modeling and simulation of electric vehicles has attracted increasing attention from researchers. This paper presents a simulation model of a full electric vehicle on the Matlab-Simulink platform to examine power flow during motoring and regeneration. The drive train components consist of a motor, a battery, a motor controller and a battery controller; modeled according to their mathematical equations. All simulation results are plotted and discussed. The torque and speed conditions during motoring and regeneration were used to determine the energy flow, and performance of the drive. This study forms the foundation for further research and development

Modeling and Simulation of Regenerative Braking Energy in DC Electric Rail Systems

Regenerative braking energy is the energy produced by a train during deceleration. When a train decelerates, the motors act as generators and produce electricity. This energy can be fed back to the third rail and consumed by other trains accelerating nearby. If there are no nearby trains, this energy is dumped as heat to avoid over voltage. Regenerative braking energy can be saved by installing energy storage systems (ESS) and reused later when it is needed. To find a suitable design, size and placement of energy storage, a good understanding of this energy is required. The aim of this paper is to model and simulate regenerative braking energy. The dc electric rail transit system model introduced in this paper includes trains, substations and rail systems

Advanced Diagnostics of Position Sensors for the Actuation Systems of High-Speed Tilting Trains

Trains tilting permits a train to travel at a high speed while maintaining an acceptable passenger ride quality with respect to the lateral acceleration, and the consequent lateral force, received by the passengers when the train travels on a curved track at a speed in excess of the balance speed built into the curve geometry. The tilting of a train carbody is performed by a control and actuation system which operates as a closed servoloop accepting the commands from the train control system, generating the torque necessary to tilt the carbody with respect to the bogie and measuring the tilt angle to close the control loop. Measurement of the tilt angle of each train vehicle is performed by two sensors located in the front and rear part of the vehicle. Since a correct tilt angle measurement is vital for the system operation and for ensuring a safe ride, in case of discrepancy between the signals of the two tilt angle sensors of any vehicle, the tilting operation is disabled and the train speed is reduced. An innovative tilt angle sensors health management system is herein presented that makes intelligent use of all available information to allow detection of malfunctioning of an individual tilt angle sensor, thereby enabling a continued operation of the tilting system and a high speed travel after a sensor failure occurs

An investigation into hybrid power trains for vehicles with regenerative braking

Imperial Users onl