Vehicle Design

This paper takes analyses electric car styling design with a focus on low aerodynamic drag. The design starts with an ideal low-drag shape, and then develops the shape into a car styling. With the method of Computational Fluid Dynamics, and after several iterations between design refinement and aerodynamic optimization, the Coefficient of Drag (CD) finally resulted in 0.19, which is quite low for electric cars for saving energy and further the driving range.

The design and optimisation of a permanent magnet-assisted synchronous reluctance (PMaSynR) traction machine is described to improve its energy efficiency over a selection of driving cycles, when installed on a four-wheel-drive electrically powered vehicle for urban use, with two on-board powertrains. The driving cycle-based optimisation is defined with the objective of minimising motor energy loss under strict size constraints, while maintaining the peak torque and restricting the torque ripple. The key design parameters that exert the most significant influence on the selected performance indicators are identified through a parametric sensitivity analysis. The optimisation brings a motor design that is characterised by an energy loss reduction of 8.2% over the WLTP Class 2 driving cycle and 11.7% over the NEDC and Artemis Urban driving cycles, at the price of a 4.7% peak torque reduction with respect to the baseline machine. Additional analysis, implemented outside the optimisation framework, revealed that different coil turn adjustments would reduce the energy loss along the considered driving cycles. However, under realistic size constraints, the optimal design solutions are the same.

In this paper a new design model of the electric vehicle is presented. This model is based on the combination of Modelica with ModelCenter. Modelica has been used to model and simulate the electric vehicle and ModelCenter has been used to optimize the design variables. The model ensures that the requirements related to driving distance and acceleration are fulfilled.

This paper presents a fast and accurate state-space model for synchronous machines taking into consideration the machine geometry, material non-linearities and core losses. The model is first constructed by storing the solutions of multiple static finite element (FE) simulations into lookup-tables (LUTs) to express the stator flux linkages as functions of the state variables, i.e., the winding currents and the rotor position. Different approaches are discussed to include the core loss into the model. A novel approach is presented for constructing a pre-computed LUT for the core loss as a function of the state variables and their time derivatives so that the loss can be directly interpolated when time-stepping the state-space model. The Simulink implementation of the proposed core-loss model shows a good match with time-stepping FE results with a 120-fold speedup in computation. In addition, comparison against calorimetric loss measurements for a 150-kVA machine operating under both sinusoidal and pulse-width modulated voltage supplies is presented to validate the model accuracy.

Multi-Moby is an ambitious project aiming at quickly finalising the results of a cluster of ongoing and past European projects, addressing the development of technologies for safe, efficient and affordable urban electric vehicles (EVs). This paper presents the developments that have been implemented in the first half of Multi-Moby, which deals with low-cost M1 and N1 EVs, to be manufactured via low-investment and lean processes and plants. The Multi-Moby EVs have excellent passive safety characteristics, enhanced by pre-emptive active safety controllers. The vehicles can be coupled with efficient 100 V or 48 V powertrains. Fast charging is enabled by the integrated design of hybrid supercapacitor-battery cells and wall box chargers. The project will also consider low-cost automated driving solutions, with focus on gimbal-based camera systems for environmental sensing and detection.

This article addresses a common issue in the design of battery electric vehicles (BEVs) by introducing a comprehensive methodology for the modeling and simulation of BEVs, referred to as the “PerfECT Design Tool”. The primary objective of this study is to provide engineers and researchers with a robust and streamlined approach for the early stages of electric vehicle (EV) design, offering valuable insights into the performance, energy consumption, current flow, and thermal behavior of these advanced automotive systems.