There are increasing interests in improving public transportation systems. One of the proposed strategies for this improvement is the use of Battery Electric Vehicles (BEVs). This approach leads to a new challenge as the BEVs’ routing is exposed to the traditional routing problems of conventional vehicles, as well as the particular requirements of the electrical technologies of BEVs. Examples of BEVs’ routing problems include the autonomy, battery degradation, and charge process. This work presents a differential evolution algorithm for solving an electric vehicle routing problem (EVRP). The formulation of the EVRP to be solved is based on a scheme to coordinate the BEVs’ routing and recharge scheduling, considering operation and battery degradation costs. A model based on the longitudinal dynamics equation of motion estimates the energy consumption of each BEV. A case study, consisting of an airport shuttle service scenario, is used to illustrate the proposed methodology. For this transport service, the BEV energy consumption is estimated based on experimentally measured driving patterns.

A low-cost experimental-numerical method for the prediction of on-road comfort of city bicycles is presented. Experimental tests are performed by exciting the wheels of the bicycle with impulsive vibrations and measuring the frequency response functions (FRFs) between different sensitive points of the bicycle (i.e. seatpost and steerer tube) and the wheels. Laboratory tests are carried out with the rider on the bicycle, and the posture is carefully checked. A mathematical model is employed to predict the accelerations experienced by the rider on the road, considering tyre and wheelbase filtering. As a verification of the proposed methodology, comfort predictions obtained with the experimental-numerical method are compared with reference data obtained from road tests. A general agreement in terms of the root mean square values and power spectral densities is found.

One of the main problems in autonomous electric vehicles is the energy storage, because of the use of low capacity batteries with low power delivery. This work shows a way to deal with the energy storage problem on a high performance electric vehicle capable to run a quarter of a mile in 10 seconds. The concept design of the system combines different storage technologies, ensuring the appropriate power delivery to the motors during the short time needed. In order to achieve this goal, it is necessary to determine the optimum size of each storage element to guarantee the vehicle high performance. This work proposes a methodology for evaluating different characteristics of ultracapacitors and batteries, such as mass, volume and cost. After determining the amount of the storage technologies, it is possible to make an optimal power management in the vehicle, that combined with the control of the motors improves the performance of the electric vehicle.

In the present paper, Computational Fluid Dynamics (CFD) simulations of the aerodynamics of a station wagon using DES (Detached Eddy Simulation), based on the Spalart-Allmaras turbulence model, are discussed and compared with experimental results. DES is a non-zonal hybrid turbulence model that uses both Reynolds Averaged Navier-Stokes (RANS) and Large Eddy Simulation (LES), enabling a better equilibrium between the accurateness and the computational cost of the solution.Simulations were run in parallel using the commercial software ANSYS/FLUENT v13.0, and required a computational grid of approximately 50 million cells. Some flow characteristics such as boundary layer separation, recirculation zones, and the entire pressure and velocity field were also obtained and analyzed. Computational results of drag force were compared with experimental results based on the SAE J1263 recommended practice (which describes a way to calculate the resistive loads that act on a vehicle during non- forced deceleration). Changes were made in the experimental estimation of the drag force, compared to the procedure stated in SAE J1263 (e.g., a differential formulation of the system was used, and the mass of the vehicle was altered by loading extra bodies into the vehicle). A selection among different sets of experimental conditions (vehicle velocities and vehicle weights) was made to improve the accuracy of the prediction.Even though computational and experimental approaches involved different models and simplifications, results from each of them showed a fair agreement. Congruence was driven by the iterative improvements made on the boundary conditions and meshing parameters on the CFD approach, and the careful experimental design performed. The aerodynamic drag coefficient calculated by CFD was of 0.460 compared to 0.404 when calculated by experimental means, which represents a 13.8% difference or 56 drag counts.

This paper presents the conceptual design of a hybrid electric off-road vehicle. The vehicle is intended to be used in Colombia (South America) where the topographical conditions require special considerations for the design of the critical systems. A study and preliminary design of the power supply system, the suspension and the powertrain are presented.