• Energy Research

Light electric vehicles are best suited for city and suburban settings, where top speed and long-distance travel are not the primary concerns. The literature concerning light electric vehicle powertrain design often overlooks the influence of the associated driving missions. Typically, the powertrain is initially parameterized, established, and then evaluated with an ex-post-performance assessment using driving cycles. Nevertheless, to optimize the size and performance of a vehicle according to its intended mission, it is essential to consider the driving cycles right from the outset, in the powertrain design. This paper presents the design of an electric powertrain for multipurpose light electric vehicles, focusing on the motor, battery, and charging requirements. The powertrain design optimization is realized from the first stages by considering the vehicle’s driving missions and operational patterns for multipurpose usage (transporting people or goods) in European urban environments. The proposed powertrain is modular and scalable in terms of the energy capacity of the battery as well as in the electric motor shaft power and torque. Having such a possibility gives one the flexibility to use the powertrain in different combinations for different vehicle categories, from L7 quadricycles to light M1 vehicles.

Zero-emission trucks for regional and long-haul missions are an option for fossil-free freight. The viability of such powertrains and system solutions was studied conceptually in project ESCALATE for trucks with GVW of 40 tonnes and beyond through various battery electric and fuel cell prime mover combinations. The study covers battery and fuel cell power sources with different degrees of battery electric as well as H2 and fuel cell operation. As a design basis, two different missions with a single-charge/H2 refill were analysed. The first mission was the VECTO long-haul profile repeated up to 750 km, whereas the second was a real 520 km on-road mission in Finland. Based on the simulated energy consumption on the driving cycle, on-board energy demand was estimated, and the initial single-charge and H2 refill operational scenarios were produced with five different power source topologies and on-board storage capacities. The traction motors of the tractor were dimensioned so that a secondary mission of GVW up to 76 tonnes on a shorter route or a longer route with more frequent battery recharge and/or H2 refill can be operated. Based on the powertrain and vehicle model, various infrastructure options for charging and H2 refuelling strategies as well as various operative scenarios with indicative total cost of ownership (TCO) were analysed.

Battery electric buses have been tested in Helsinki region to gain experience on the actual energy consumption and how well they suit for the Finnish climate. Measurements were performed on a chassis dynamometer with various driving cycles and gross vehicle weights in order to be able to analyse the buses in detail. The measurements reveal significant differences in the energy consumption of the buses. The sensitivity to different cycles and loads also varies greatly. The observed differences can partly be explained by the different curb weights of the buses. Another reason for the differences is the regeneration rate, which was as low as 15% for some buses, while the best bus was able to regenerate over 35% of the energy.

The paper presents use case simulations of fleets of electric buses in two cities in Europe, one with a warm Mediterranean climate and the other with a Northern European (cool temperate) climate, to compare the different climatic effects of the thermal management strategy and charging management strategy. Two bus routes are selected in each city, and the effects of their speed, elevation, and passenger profiles on the energy and thermal management strategy of vehicles are evaluated. A multi-objective optimization technique, the improved Simple Optimization technique, and a “brute-force” Monte Carlo technique were employed to determine the optimal number of chargers and charging power to minimize the total cost of operation of the fleet and the impact on the grid, while ensuring that all the buses in the fleet are able to realize their trips throughout the day and keeping the battery SoC within the constraints designated by the manufacturer. A mix of four different types of buses with different battery capacities and electric motor specifications constitute the bus fleet, and the effects that they have on charging priority are evaluated. Finally, different energy management strategies, including economy (ECO) features, such as ECO-comfort, ECO-driving, and ECO-charging, and their effects on the overall optimization are investigated. The single bus results indicate that 12 m buses have a significant battery capacity, allowing for multiple trips within their designated routes, while 18 m buses only have the battery capacity to allow for one or two trips. The fleet results for Barcelona city indicate an energy requirement of 4.42 GWh per year for a fleet of 36 buses, while for Gothenburg, the energy requirement is 5 GWh per year for a fleet of 20 buses. The higher energy requirement in Gothenburg can be attributed to the higher average velocities of the bus routes in Gothenburg, compared to those of the bus routes in Barcelona city. However, applying ECO-features can reduce the energy consumption by 15% in Barcelona city and by 40% in Gothenburg. The significant reduction in Gothenburg is due to the more effective application of the ECO-driving and ECO-charging strategies. The application of ECO-charging also reduces the average grid load by more than 10%, while shifting the charging towards non-peak hours. Finally, the optimization process results in a reduction of the total fleet energy consumption of up to 30% in Barcelona city, while in Gothenburg, the total cost of ownership of the fleet is reduced by 9%.

Charging Management Strategy is a critical aspect in electric bus fleets to minimize the impact on the local electricity grid and to minimize the financial cost to the bus operators. To realize a fleet of battery electric public transport buses in a city depends on two major stakeholders, namely the city bus operator and the electricity distribution systems operator. The cost of the electric charging infrastructure, including the high powered ultrafast DC chargers for opportunity charging and lower powered depot chargers for overnight charging is a significant investment for the city bus operator in terms of capital, installation, and grid connection costs, while the distribution system operator has to contend with significant power load on the electricity grid when multiple ultrafast chargers are in operation. This paper investigates a Use Case of an electric bus fleet plying a route, and the optimal selection of chargers, charging duration, and battery State of Charge that will minimize the impact on the local grid and minimize the total cost of ownership. A Simple Optimization algorithm was utilized for this purpose. Results show that the objectives are mutually exclusive, and there need to be a tradeoff to achieve the optimal balance between grid impact and total cost of ownership. Results also show that grid impact and the total cost of ownership are both minimized when opting for low c-rate charging instead of high c-rate charging or when charging only for short durations. Finally, an ECO-charging technique based on utilizing short-duration pulsed charging followed by cool-down periods instead of charging in one continuous long-duration pulse was investigated to determine its efficacy in lowering the energy requirements of the bus by reducing the battery heat generation due to high c-rate charging. The optimum charging-to-cooldown ratio and the optimum charging pulse was found using brute force method to determine the lowest cooling energy consumption for a variety of charging rates. Results show that up to 5% reduction in grid impact can be achieved due to implementation of ECO-charging technique.

The paper proposes an identification method for the inductances of induction machines, based on signal injection. Due to magnetic saturation, a saturation-induced saliency appears in the induction motor, and the total leakage inductance estimate depends on the angle of the excitation signal. The proposed identification method is based on a small-signal model that includes the saturation-induced saliency. Because of the saturation, the load also affects the estimate, and measurements are needed in different operating points. Using the identified total leakage inductance, an estimate of the stator inductance can be obtained. The identification method is applied to computer simulations and laboratory experiments of a 2.2-kW induction motor.

An induction machine model is proposed for the identification of rotor parameters using high-frequency signal injection. The model includes both the magnetic saturation caused by the fundamental-wave components and the frequency dependence encountered in the signal injection method. Both the skin effect in the rotor winding and the eddy current losses in the rotor core are taken into account. Sinusoidal signal injection is used at several frequencies, and the model parameters are fitted to the results. The rotor leakage inductance and the rotor resistance valid at low slip frequencies are also obtained from the model directly. Experimental results for a 45-kW machine are presented. It is shown that the model fits well to the measured data in various operating points, and the accuracy of the identified parameters is good.