Development of an optimal strategy for the energy management of a range-extended electric vehicle with additional noise, vibration and harshness constraints

Abstract

Nowadays, electric vehicles represent a promising solution for reducing the fuel consumption (and thus the carbon dioxide emission) and the pollutant emissions of road vehicles, especially in highly congested urban areas, although their driving range and usability still limit the customer acceptance even for a city car application. Extended-range electric vehicles may partly overcome these limitations, having an auxiliary power unit which can provide electrical energy to the powertrain once the battery has been depleted. On the other hand, the operations of such an auxiliary power unit should be almost completely unnoticeable in order to avoid any impacts on the electric driving experience, resulting in considerably reduced drive-related noise. Therefore the aim of this work is the design, through numerical simulation, of a powertrain controller capable of minimizing the carbon dioxide emission of a range-extended electric vehicle and, at the same time, avoiding any discomfort for the passenger related to the auxiliary power unit operations. Starting from the development of a powertrain controller focused on minimization of the carbon dioxide emission of the vehicle, the main noise targets will be defined and their effects on the energy management system will be analysed.

Investigation into a stepped-piston engine solution for automotive range-extender vehicles and hybrid electric vehicles to meet future green transportation objectives

“…Installation within a semi anechoic power plant cell could also assist reduction of the well reported negative NVH characteristics of periodic power plant operation which is typical of RE-EVs and HEVs. The unexpected start up of the IC engine unit often provides an unexpected and unwanted noise source within the vehicle structure and destroys the near silent driving experience as discussed by Millo et al [30]. Application of a partially insulated noise cell could minimise this negative vehicle characteristic in RE-EVs and HEVs offering the potential for low emission high efficiency transportation in a low cost small vehicle.…”

Energy Management on Compound Storage System in Electric Vehicle with Longitudinal Dynamics

“…Take isolated body from the various parts of the car, and take the driven wheel, the driving wheel and the rest of the car to force analysis [5].…”

Energy flow analysis of an electric city bus based on wavelet transform with Mallet prolongation

“…In addition, in the study of Carter et al, the rule‐based control strategy is proposed, but the method is analyzed from the cost performance further without the whole vehicle performance; the dual closed‐loop control structure is adopted, the outer loop is used to acquire the best size of HESS, although the algorithm parameters are adjusted in the inner loop, the structure is depended on the rules, and the results cannot be optimized . In recent years, the intelligent control methods such as neural network and fuzzy control are also applied in vehicle energy management technology, when the fuel consumption and gas emissions are as design indicators; the data of different road cycles can be trained to predicted the vehicle behavior on the neural network model; the neural network is used to predict road cycles and traffic jam degree online for energy management; in the study of Millo et al, the energy management system for hybrid electric vehicle (HEV) with HESS is developed on the neural network; in the study of Marie et al, the neural network is used to manage the power flow between the storage energy system and the load. Fuzzy control has strong robustness, which is applied in the vehicle management strategy; in the fuzzy controller, the control rules are designed based on the driving command, the state of charge (SOC) of the battery, and the vehicle speed; the output variables are the reasonable power distribution between the motor and the engine; the aim of adopting fuzzy control is to optimize the drive system and improve the battery recovery efficiency; in the study of Dawei et al, the fuzzy energy management strategy is used to the power flow for uniaxial parallel hybrid vehicle; the membership functions in the controller are optimized by genetic algorithm; the results show fuzzy control can effectively avoid the production of the engine peak torque and improve the overall vehicle performance.…”