A Novel Approach of Improving Battery Performance and Longevity of the Developed Electrically Assisted Triwheeler Vehicle by Implementing Torque Sensor Technology

This paper presents a new approach to improving the battery performance and its longevity by the implementation of torque sensor pedal technology on the developed electric triwheeler vehicle (i.e., wheelchair). The paper has also discussed integration of the torque sensor technology with the overall electrical system of the vehicle. Incorporating the components of torque sensor technology reduces the human effort immensely by providing assistance from the battery bank to drive a hub motor while maneuvering the wheelchair using the torque sensor pedal. Field tests were carried out in three different stages, one with pedal, one with the throttle only, and with varying the load on the wheelchair, to distinguish the effect of load test on battery performance using the pedal. Results of the field tests reveal that the state of charge of batteries has been minimized using the pedal due to the contribution of the muscular energy of the user along with the battery energy to meet the total energy demand of the motor. Analyzing test results with the torque sensor pedal clarifies that the vehicle covers a longer distance, lessens power dissipation from the batteries, and reduces energy consumption from the batteries, which leads to improvement of the battery performance and its longevity ensuring sustainability of the electric vehicle.

Integration of an Adaptive Infotainment System in a Vehicle and Validation in Real Driving Scenarios

More services, functionalities, and interfaces are increasingly being incorporated into current vehicles and may overload the driver capacity to perform primary driving tasks adequately. For this reason, a strategy for easing driver interaction with the infotainment system must be defined, and a good balance between road safety and driver experience must also be achieved. An adaptive Human Machine Interface (HMI) that manages the presentation of information and restricts drivers’ interaction in accordance with the driving complexity was designed and evaluated. For this purpose, the driving complexity value employed as a reference was computed by a predictive model, and the adaptive interface was designed following a set of proposed HMI principles. The system was validated performing acceptance and usability tests in real driving scenarios. Results showed the system performs well in real driving scenarios. Also, positive feedbacks were received from participants endorsing the benefits of integrating this kind of system as regards driving experience and road safety.

Driver Behavior Modeling: Developments and Future Directions

The advances in wireless communication schemes, mobile cloud and fog computing, and context-aware services boost a growing interest in the design, development, and deployment of driver behavior models for emerging applications. Despite the progressive advancements in various aspects of driver behavior modeling (DBM), only limited work can be found that reviews the growing body of literature, which only targets a subset of DBM processes. Thus a more general review of the diverse aspects of DBM, with an emphasis on the most recent developments, is needed. In this paper, we provide an overview of advances of in-vehicle and smartphone sensing capabilities and communication and recent applications and services of DBM and emphasize research challenges and key future directions.

Experimental Test of Artificial Potential Field-Based Automobiles Automated Perpendicular Parking

Automobiles automated perpendicular parking using Artificial Potential Field (APF) is discussed in this paper. The Unmanned Ground Vehicle (UGV) used for carrying out experiments is introduced first; UGV configuration, kinematics, and motion controller are included. Based on discretized form of the parking space, the APF is generated. Holonomic path for the vehicle parking is found first; path modification to satisfy minimum turning-radius constraint is performed based on Reeds-Shepp curve connections. Optimization efforts are included to remove extra maneuvers and to reduce length of the path. Afterwards waypoints are generated as reference for the vehicle to track. Perpendicular parking tests with several different start configurations are demonstrated; based on the test results the automated parking framework proposed in this paper is considered to be effective.

Enhancing V2X Communication Based on a New Comb-Pilot Estimation Approach

Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communication systems, known as V2X technologies, have increasingly attracted attention in current research on road safety and traffic ergonomics. The performance evaluation of these communication systems is an important step before their potential integration and use in real systems. V2X communications are based on the IEEE 802.11p standard also known as Wireless Access in Vehicular Environment (WAVE). V2X can affect human life; therefore a deep study related to V2X performance evaluation should be done in order to be sure about the system reliability. In this context, we have elaborated a deep study related to the effect of transmission range on V2X communications by considering the terminal mobility. First, we have evaluated the performance of the PHY layer on the IEEE 802.11p using simulation. Secondly, we have conducted real case measurements using the Arada LocoMate Transmission system. The obtained results shows the necessity to optimize the quality of transmission in V2X communications. Consequently, we propose in this paper a new comb-pilot technique to enhance the quality of Orthogonal Frequency Division Multiplexing (OFDM) transmission. Our proposal consists in two new uses of the pilot subcarrier estimation technique in order to decrease the elevated bit error rate (BER). The quality of transmission (QoT) is first evaluated relating to the pilot symbol rearranged positions. Second, we proposed to optimize the QoT by adding two supplementary pilot symbols as it can offer better channel estimation results. Based on the performance evaluation of our proposal, it is confirmed that both of rearrangement and the adding of the pilot patterns lead to performance enhancement compared to baseline model (standardized one).

Numerical Simulation Analysis of an Oversteer In-Wheel Small Electric Vehicle Integrated with Four-Wheel Drive and Independent Steering

Similar to conventional vehicle, most in-wheel small EVs that exist today are designed with understeer (US) characteristic. They are safer on the road but possess poor cornering performance. With recent in-wheel motor and steer-by wire technology, high cornering performance vehicle does not limit to sport or racing cars. We believe that oversteer (OS) design approach for in-wheel small EV can increase the steering performance of the vehicle. However, one disadvantage is that OS vehicle has a stability limit velocity. In this paper, we proposed a Four-Wheel Drive and Independent Steering (4WDIS) for in-wheel small EV with OS characteristic. The aim of implementing 4WDIS is to develop a high steer controllability and stability of the EV at any velocity. This paper analyses the performance of OS in-wheel small EV with 4WDIS by using numerical simulation. Two cornering conditions were simulated which are (1) steady-state cornering at below critical velocity and (2) steady-state cornering over critical velocity. The objective of the simulation is to understand the behavior of OS in-wheel small EV and the advantages of implementing the 4WDIS. The results show that an in-wheel small EV can achieve high cornering performance at low speed while maintaining stability at high speed.

Modeling, Validation, and Control of Electronically Actuated Pitman Arm Steering for Armored Vehicle

In this study, 2 DOF mathematical models of Pitman arm steering system are derived using Newton’s law of motion and modeled in MATLAB/SIMULINK software. The developed steering model is included with a DC motor model which is directly attached to the steering column. The Pitman arm steering model is then validated with actual Pitman arm steering test rig using various lateral inputs such as double lane change, step steer, and slalom test. Meanwhile, a position tracking control method has been used in order to evaluate the effectiveness of the validated model to be implemented in active safety system of a heavy vehicle. The similar method has been used to test the actual Pitman arm steering mechanism using hardware-in-the-loop simulation (HILS) technique. Additional friction compensation is added in the HILS technique in order to minimize the frictional effects that occur in the mechanical configuration of the DC motor and Pitman arm steering. The performance of the electronically actuated Pitman arm steering system can be used to develop a firing-on-the-move actuator (FOMA) for an armored vehicle. The FOMA can be used as an active safety system to reject unwanted yaw motion due to the firing force.

Energy Management Strategy Implementation for Hybrid Electric Vehicles Using Genetic Algorithm Tuned Pontryagin’s Minimum Principle Controller

To reduce apace extraction of natural resources, to plummet the toxic emissions, and to increase the fuel economy for road transportation, hybrid vehicles are found to be promising. Hybrid vehicles use batteries and engine to propel the vehicle which minimizes dependence on liquid fuels. Battery is an important component of hybrid vehicles and is mainly characterized by its state of charge level. Here a modified state of charge estimation algorithm is applied, which includes not only coulomb counting but also open circuit voltage, weighting factor, and correction factor to track the run time state of charge efficiently. Further, presence of battery and engine together needs a prevailing power split scheme for their efficient utilization. In this paper, a fuel efficient energy management strategy for power-split hybrid electric vehicle using modified state of charge estimation method is developed. Here, the optimal values of various governing parameters are firstly computed with genetic algorithm and then fed to Pontryagin’s minimum principle to decide the threshold power at which engine is turned on. This process makes the proposed method robust and provides better chance to improve the fuel efficiency. Engine efficient operating region is identified to operate vehicle in efficient regions and reduce fuel consumption.

Application of Genetic Algorithms for Driverless Subway Train Energy Optimization

After an introduction on the basic aspects of electric railway transports, focusing mainly on driverless subways and their related automation systems (ATC, ATP, and ATO), a technique for energy optimization of the train movement through their control using genetic algorithms will be presented. Genetic algorithms are a heuristic search and iterative stochastic method used in computing to find exact or approximate solutions to optimization problems. This optimization process has been calculated and tested on a real subway line in Milan through the implementation of a dedicated Matlab code. The so-defined algorithm provides the optimization of the trains movement through a coast control table created by the use of a genetic algorithm that minimizes the energy consumption and the train scheduled time. The obtained results suggest that the method is promising in minimizing the energy consumption of the electric trains.