Figure 3 - available via license: Creative Commons Attribution 4.0 International
Content may be subject to copyright.
Source publication
An iterative algorithm is proposed for determining the optimal chassis design of an electric vehicle, given a path and a reference time. The proposed algorithm balances the capacity of the battery pack and the dynamic properties of the chassis, seeking to optimize the tradeoff between the mass of the vehicle, its energy consumption, and the travel...
Context in source publication
Context 1
... electric motor is responsible for converting electrical energy into mechanical energy, consuming the stored power in the battery in order to move the transmission set. The behavior (Figure 3) of the motor defines the speed, torque and other important variables for the performance of the vehicle. To mathematically define the powertrain of an electric vehicle, the starting point is the maximum torque and power values of the motor. ...
Similar publications
![Forecast of annual sales of electric vehicles (based on Bloomberg [3])](publication/346533463/figure/fig2/AS:963964884221953@1606838546965/Forecast-of-annual-sales-of-electric-vehicles-based-on-Bloomberg-3_Q320.jpg)
The automotive market is changing. For many years, cars with internal-combustion engines were dominant. Recently, more cars with alternative drive trains have become available, and their market share has increased, a trend that has had an effect on the remanufacturing industry for automotive parts. This paper aims to describe and evaluate the chall...
Citations
... In [19] some techniques have been suggested to design a minor electric vehicle chassis to reduce electricity consumption. In [20] the subject of the electric vehicle charging has been countered by proposing some smart charging techniques. Intelligent charging can work in unidirectional & bidirectional modes. ...
... Luque P et al. proposed an iterative algorithm for determining the optimal chassis design for an electric vehicle given a path and reference time. The proposed algorithm balances the capacity of the battery pack with the dynamic characteristics of the chassis and seeks to optimize the trade-off between vehicle mass, energy consumption, and travel time [14]. Liang Y et al. proposed a scalable vehicle state estimation concept that fuses conventional vehicle sensors with environmental sensors using the Error State Extended Kalman Filter (ESEKF) to ensure the accuracy and robustness of redundant sensor data under conventional and dynamic driving conditions [15]. ...
... 14, respectively, show the longitudinal speed, lateral acceleration, yaw rate, and roll angle output of the distributed drive electric vehicle Carsim/Simulink joint model and real vehicle under test conditions. It can be clearly seen that the output data of the model and the real car are basically fitted under the same working condition, which fully shows that the dynamic characteristics of the distributed drive electric vehicle Carsim/Simulink joint model are very close to that of the real car. ...
Most of the research on driving stability control of distributed drive electric vehicles is based on a yaw motion design controller. The designed controller can improve the lateral stability of the vehicle well but rarely mentions its changes to the roll and pitch motion of the body, and the uneven distribution of the driving force will also cause instability in the vehicle speed, resulting in wheel transition slip, wheel sideslip, and vehicle stability loss. In order to improve the spatial stability of distributed-driven electric vehicles and resolve the control instability caused by their motion coupling, a decoupled control strategy of yaw, roll, and pitch motion based on multi-objective constraints was proposed. The strategy adopts hierarchical control logic. At the upper level, a yaw motion controller based on robust model predictive control, a roll motion controller, and a pitch motion controller based on feedback optimal control are designed. In the lower level, through the motion coupling analysis of the vehicle yaw control process, based on the coupling analysis, the vehicle yaw, roll, and pitch decoupling controller based on multi-objective constraints is designed. Finally, the effectiveness of the decoupling controller is verified.
... The chassis serves as the backbone of any vehicle, providing structural integrity while affecting key parameters such as strength, safety, and efficiency [4]. In the realm of EVs, the role of the chassis becomes more complex due to the necessity to incorporate various components like batteries, electric motors, and power electronics efficiently [5]. These complexities are magnified in designing EVs for urban settings, where the demand for compactness, efficiency, and short-range operability is high [6,7]. ...
This paper focuses on the design and evaluation of hollow frame structures for the development of two-passenger electric vehicles targeted for urban use. The primary problem addressed is the lack of focused research on efficient, lightweight, and safe electric vehicle frame designs, particularly for urban transportation needs. Through 3D simulation and Finite Element Analysis (FEA), this paper successfully develops a hollow frame design with dimensions of 2,148×800×640 mm and a weight of 40.77 kg that meets strength and stiffness criteria. The analysis shows that the design has an adequate safety margin with a safety factor of 2.053e+01. ASTM A36 steel is chosen as the material, balancing strength, stiffness, and cost. The results offer an innovative and practical solution to urban transportation issues, with broad potential applications in the electric vehicle industry. In particular, this study focuses on the specialized needs of urban-centric, two-passenger electric vehicles. The Finite Element Analysis (FEA) used here serves as a robust validation method, effectively reducing the need for extensive physical testing. This accelerates the R&D process and opens possibilities for future studies on alternative materials and dynamic loading conditions. The study's limitations and future research directions are also discussed. Moreover, the study's computational methods offer an eco-friendly alternative to traditional physical prototypes. This aligns with sustainability goals and provides methodologies for future studies. With rising urban populations, the demand for efficient vehicles is increasing. This study paves the way for city-focused, two-passenger electric cars that meet modern urban needs and sustainability goals
... While also designing the bodies of the vehicle in a CAD software [5]. In contrast to studies that focus extensively on the design analysis of electric vehicle chassis employing specific methodologies [6], the approach of the present research is rooted in the Axiomatic Design Theory and the application of Language Models applied to the case study. ...
The design process of a chassis for a high-efficiency vehicle involves considering several unique parameters due to its distinct operational needs. The constraints specified in the official regulations for the Shell Eco-Marathon prototype battery electric class could ostensibly limit design innovations. However, this paper introduces a methodological approach employing Machine Learning, facilitated by Large Language Models, which substan- tially broadens the spectrum of conceptual design possibilities. Further, the widely recognized technique of Computer-Aided Design, coupled with Generative Design, is leveraged to optimize specific sections of the chassis structure. The final stage of this study involves rigorous testing of the designed chassis to assess its mechanical performance, guided by the stringent benchmarks set by the competition.
... Moreover, it seeks to optimize the tradeoff between the mass of the vehicle, its energy consumption, and the travel time. The design variables of the chassis include geometrical and inertial values, as well as the characteristics of the powertrain [2]. ...
Vehicle technology with an internal combustion engine emerged at the end of the 19th century. Although it is not very well known, the first prototype studies of the electric vehicle coincide with the same period. Today, factors such as global warming, pollution and the decrease in fossil fuel reserves accelerate the transition to electric vehicle technology. In this context, a new system structure is needed for electrically driven systems differently from traditional vehicle structures. In this study, a chassis design for an electric vehicle is carried out. While designing, the part where the battery pack will be placed has been modeled and simulated with the help of the ANSYS program to protect the battery and electronic components that are particularly sensitive to impacts. In order to be successful in abuse tests such as Crush and Crash tests specified in the regulations and standards, the material selection and design should be done correctly. In this context, the right materials are determined as a result of the researches and 3D simulations are made and crash tests are carried out in the simulation environment. As a result, tube type chassis was chosen among many chassis models and 7079 aluminum alloy was found suitable as raw material. According to the simulation results, it is seen that the design and the selected alloy are suitable.
... The GA is well suited for driving strategy-related tasks because it can effectively solve complex, nonlinear, and greybox problems. The GA has been applied to minimize energy in various similar applications with great success [7,21,22]. Figure 5 shows the resulting optimized braking-torque function displayed in the efficiency map of the powertrain in generator operation. In the figure, the resulting torque values are indicated with black dots. ...
... The GA is well suited for driving strategy-related tasks because it can effectively solve complex, nonlinear, and grey-box problems. The GA has been applied to minimize energy in various similar applications with great success [7,21,22]. Figure 5 shows the resulting optimized brakingtorque function displayed in the efficiency map of the powertrain in generator operation. In the figure, the resulting torque values are indicated with black dots. ...
... The number of optimization variables (n var ) is calculated from the track length according to Equation (21) and it decomposes the track distance into elements, thus forming the s distance vector, as shown in Equation (22). A vector interval of 10 m was chosen for practical reasons. ...
In this paper, determination of optimized regenerative braking-torque function and application in energy efficient driving strategies is presented. The study investigates a lightweight electric vehicle developed for the Shell Eco-Marathon. The measurement-based simulation model was implemented in the MATLAB/Simulink environment and used to establish the optimization. The optimization of braking-torque function was performed to maximize the recuperated energy. The determined braking-torque function was applied in a driving strategy optimization framework. The extended driving strategy optimization model is suitable for energy consumption minimization in a designated track. The driving strategy optimization was created for the TT Circuit Assen, where the 2022 Shell Eco-Marathon competition was hosted. The extended optimization resulted in a 2.97% improvement in energy consumption when compared to the result previously achieved, which shows the feasibility of the proposed methodology and optimization model.
... This is because the T6-treated alloys undergo artificial aging, a treatment that requires a higher energy expenditure. In this heat treatment, the alloys are solubilized and subsequently heated between 100 °C and 200 °C so that the atoms diffuse and precipitation of hardening phases could happen, optimizing the mechanical properties 7,9 . Therefore, this need for a prolonged heating of the parts may generate a higher energy spending than that associated with the production of alloys in T4 condition, which underwent only solubilization treatment, while the aging is carried out at room temperature (naturally). ...
The market for electric vehicles is growing, seen as the best alternative to replace internal combustion-powered vehicles. Recent developments in electric vehicles have allowed them to reach a level of performance, comfort, and safety that enables them to compete with traditional vehicles. However, several studies are directed towards increasing the autonomy of these vehicles, aiming at weight reduction of structural components. Aluminum alloys are increasingly being chosen to produce structural elements, due to their low density and suitable properties. The 6000 Al alloys are often used in chassis and bodywork. In view of this, this work proposes a comparison of 6000 series alloys, by means of thermodynamic (using Thermo-Calc®) and property computations (Ansys® Granta EduPack and Selector) to select the best alloys considering application properties, processability, and environmental impact. It was observed that the T6 heat-treated alloys presented better mechanical properties, but, on the other hand, they have more impact on the environment. As such, the 6010-T6 alloy was classified as the best alloy regarding performance, the 6061-T4 alloy the best in terms of processability, and the 6009-T4 alloy presented the lowest environmental impact. The 6111-T4 alloy was highlighted as the alloy showing the best balance between the examined properties.
... The first step was to calculate the instantaneous power required to achieve the kinematic response for the vehicle being measured [38]. It is known that at each step during the test the tractive force shall be such that it counteracts total driving resistance and causes the vehicle to accelerate as required. ...
Worldwide, cities hold a preeminent position in the global economy and human activity, but their growth poses considerable challenges to sustainability. Parallel to the current trends of population growth and urbanization, the process of digitalization and the technological revolution promote a further increase in e-commerce transactions, which have emerged as a critical component in the debate over the future of cities. More people living in cities and more people transacting online translates into more demand for in-city delivery, with the consequent increase in land occupation, pollution, and reduction of liveability to name a few.
Last-mile delivery (LMD) is the last chapter of the logistic chain, in which the parcel is delivered to the end consumer. Thus, LMD operations vary according to the context, e.g, urban setting, road network, and product delivered. Furthermore, they involve the interaction between multiple stakeholders with different and frequently conflicting interests and objectives. In this context, the literature points out (i) a lack of real data which would help to define efficient policy measures for LMD in different urban settings, and (ii) the necessity to consider different stakeholder perspectives for efficient management and planning of LMD strategies. To that end, the thesis combines quantitative and qualitative techniques. First, real data of LMD operations carried out in different urban settings are analysed and the extent to which distribution operations vary according to delivery area is presented. Then, an energy consumption model is calibrated, and fuel consumption and pollutant emissions proper of LMD operations are estimated. Second, different strategies are
assessed for improving e-commerce LMD efficiency, and their strengths and
weaknesses are explored. To this scope, an online Multi-Actor Multi-Criteria evaluation is performed.
The results highlight the urgency of (i) replacing LDVs with non-motorised modes in city centres and suburban residential areas, and (ii) implementing intermodality and electric fleets in suburban areas. Considering both qualitative and quantitative analysis, it emerges that increasing parcel lockers in the cities would solve most of the inefficiencies identified and would receive the most consensus from stakeholders. This thesis provides a holistic perspective of the LMD problem in urban areas while promoting a bottom-up approach that considers different aspects of LMD operations. On the one hand, it gives empirical knowledge on the challenges that LMDs bring to the improvement of the liveability of cities. On the other hand, it seeks to ease the decisionmaking process for implementing strategies aimed at reducing LMD impacts in urban areas. The findings yield interesting conclusions and useful policy recommendations that could bring to more efficient and sustainable LMD operations.
... Nowadays, energy efficiency in automotive applications is being considered. In some applications which implicate inefficient acceleration and deceleration of internal combustion vehicles, such as mining, an electric vehicle can be used in a very efficient way [1]. Electric vehicles have components that are more delicate than regular combustion vehicles, such as batteries and other high voltage electrical components. ...
In this paper, the analysis of engine mounting structures that will be applied to electric vehicles is conducted. The engine mounting structure will be subjected to static loading from the mounted components assembly, including the assembly of the gearbox, electric motor, and corresponding brackets. In the structure arrangement, HSLA material is mostly used and general structural steel such as AISI 4130 is also used. This study aims to evaluate the existing design so that further optimization steps can be carried out. Simulations and analysis with a static approach were performed using SOLIDWORKS. The stress and displacement contours are then created, and the location of the critical points of maximum stress and maximum deflection can be obtained so that the safety factor of the design can be evaluated. Based on the simulation results, the current safety factor value is very high when compared to using materials with lower physical properties. In addition, it is necessary to develop further studies involving dynamic loading so that it can also be considered to reduce production costs and increase production efficiency.
... It can be seen the appropriateness of developing an optimization method, that defines the optimal powertrain for an electric vehicle and a determined route (Luque, 2020). An already defined path and time, allows the designer to find a solution adapted to the specific need of the vehicle (Valle, 2018). ...
The global challenge of reducing pollutant and greenhouse gas emissions has forced the development of alternatives to traditional internal combustion engine vehicles, such as electric or hybrid vehicles. Electric engines are the most efficient for delivery trucks or city buses. Their acceleration and deceleration patterns make them inefficient for the use of internal combustion engines. However, their range and purchase cost are the main factors limiting their use in these applications. The range and acquisition cost of an electric vehicle are mainly related to the energy storage system. Therefore, the optimal size of the battery pack should be considered as a design objective when its application is known. This paper presents a methodology to optimize the battery pack of an electric vehicle based on a given travel distance in a target time. Therefore, it would be applicable to delivery vehicles, buses and any vehicle whose route and travel time are known in advance. The proposed methodology allows minimizing energy consumption by determining the optimal gear ratio for a given route, setting the travel time as a target. A complete vehicle model and a multi-objective genetic algorithm are used for this purpose.
