Design and evaluation of a real-time fuel-optimal control system for series hybrid electric vehicles

Razavian, R. S., Taghavipour, A., Azad, N. L., & McPhee, J. (2012). Design and evaluation of a real-time fuel-optimal control system for series hybrid electric vehicles. International Journal of Electric and Hybrid Vehicles, 4(3), 260. Final version published by Inderscience Publishers, and available at: https://doi.org/10.1504/IJEHV.2012.050501We propose a real-time optimal controller that will reduce fuel consumption in a series hybrid electric vehicle (HEV). This real-time drive cycle-independent controller is designed using a control-oriented model and Pontryagin's minimum principle for an off-line optimisation problem, and is shown to be optimal in real-time applications. Like other proposed controllers in the literature, this controller still requires some information about future driving conditions, but the amount of information is reduced. Although the controller design procedure explained here is based on a series HEV with NiMH battery as the electric energy storage, the same procedure can be used to find the supervisory controller for a series HEV with an ultra-capacitor. To evaluate the performance of the model-based controller, it is coupled to a high-fidelity series HEV model that includes physics-based component models and low-level controllers. The simulation results show that the simplified control-oriented model is accurate enough in predicting real vehicle behaviour, and final fuel consumption can be reduced using the model-based controller. Such a reduction in HEVs fuel consumption will significantly contribute to nationwide fuel saving.The authors would like to thank the Natural Sciences and Engineering Research Council (NSERC) of Canada, Toyota, and Maplesoft for their support of this research

Urban and extra-urban hybrid vehicles: a technological review

Pollution derived from transportation systems is a worldwide, timelier issue than ever. The abatement actions of harmful substances in the air are on the agenda and they are necessary today to safeguard our welfare and that of the planet. Environmental pollution in large cities is approximately 20% due to the transportation system. In addition, private traffic contributes greatly to city pollution. Further, “vehicle operating life” is most often exceeded and vehicle emissions do not comply with European antipollution standards. It becomes mandatory to find a solution that respects the environment and, realize an appropriate transportation service to the customers. New technologies related to hybrid –electric engines are making great strides in reducing emissions, and the funds allocated by public authorities should be addressed. In addition, the use (implementation) of new technologies is also convenient from an economic point of view. In fact, by implementing the use of hybrid vehicles, fuel consumption can be reduced. The different hybrid configurations presented refer to such a series architecture, developed by the researchers and Research and Development groups. Regarding energy flows, different strategy logic or vehicle management units have been illustrated. Various configurations and vehicles were studied by simulating different driving cycles, both European approval and homologation and customer ones (typically municipal and university). The simulations have provided guidance on the optimal proposed configuration and information on the component to be used

Predictive control for energy management in all/more electric vehicles with multiple energy storage units

The paper describes the application of Model Predictive Control (MPC) methodologies for application to electric and hybrid-electric vehicle drive-train formats incorporating multiple energy/power sources. Particular emphasis is given to the co-ordinated management of energy flow from the multiple sources to address issues of extended vehicle range and battery life-time for all-electric drive-trains, and emissions reduction and drive-train torsional oscillations, for hybrid-electric counterparts, whilst accommodating operational constraints and, ultimately, generic non-standard driving cycles

The Development of Motor Tandem Axle Module in Series Hybrid Commercial Vehicles

The growing issues of energy shortage and the environmental crisis have resulted in new challenges for the automotive industry. Conventional commercial vehicles such as refuse trucks and delivery vehicles consume significantly more energy than other on-road vehicles and emit more emissions. It is important to make these vehicles more fuel efficient and environmentally friendly. Hybrid power-trains provide a good solution for commercial vehicles because they not only provide optimum dynamic properties but also substantially reduce emissions. For most commercial vehicle power-trains, the internal combustion engine (ICE) is the only power source that provides power to the drive-line. The emission reduction faces a limit since a high-powered engine is required to meet the dynamic properties of those heavy-duty vehicles. Also, the high-powered engine cannot avoid operating in low efficient areas due to the fact that these vehicles continually drive at low speeds on designated city routes. However, hybrid power-trains allow commercial vehicles to select lower powered engines because they are equipped with multi-power sources to supply torque together to the drive-line. Therefore, hybrid power-trains are a natural fit for commercial vehicles. For this reason, an alternative series hybrid drive-train system, which contains an electric tandem axle module, has been designed for those heavy-duty commercial vehicles like city transits and refuse trucks. In order to prove the theoretical efficiency and practicability of this application, the modeling methodology for specification of system architectures and hybrid drive-train control strategies will be provided in this paper with the demonstration of simulation methods and results

Energy harvesting from vehicular traffic over speed bumps: A review

Energy used by vehicles to slow down in areas of limited speed is wasted. A traffic energy-harvesting device (TEHD) is capable of harvesting vehicle energy when passing over a speed bump. This paper presents a classification of the different technologies used in the existing TEHDs. Moreover, an estimation of the energy that could be harvested with the different technologies and their cost has been elaborated. The energy recovered with these devices could be used for marking and lighting of roads in urban areas, making transportation infrastructures more sustainable and environmentally friendly

Observer techniques for estimating the state-of-charge and state-of-health of VRLABs for hybrid electric vehicles

The paper describes the application of observer-based state-estimation techniques for the real-time prediction of state-of-charge (SoC) and state-of-health (SoH) of lead-acid cells. Specifically, an approach based on the well-known Kalman filter, is employed, to estimate SoC, and the subsequent use of the EKF to accommodate model non-linearities to predict battery SoH. The underlying dynamic behaviour of each cell is based on a generic Randles' equivalent circuit comprising of two-capacitors (bulk and surface) and three resistors, (terminal, transfer and self-discharging). The presented techniques are shown to correct for offset, drift and long-term state divergence-an unfortunate feature of employing stand-alone models and more traditional coulomb-counting techniques. Measurements using real-time road data are used to compare the performance of conventional integration-based methods for estimating SoC, with those predicted from the presented state estimation schemes. Results show that the proposed methodologies are superior with SoC being estimated to be within 1% of measured. Moreover, by accounting for the nonlinearities present within the dynamic cell model, the application of an EKF is shown to provide verifiable indications of SoH of the cell pack

Virtual laboratories on energy management systems: the Hybrid Electric Vehicle case

Due to environment and social needs, energy management is becoming a key easy which must be transversely introduced to engineering students. Unfortunately most of this topics are difficult to analyze in traditional laboratories, this paper presents a virtual laboratory on Hybrid Electrical Vehicles specially designed to illustrate the power flow and the energy management algorithms involved in this type of device. The paper describes the models behind the interactive virtual laboratory, the different configurations which can be taken into account and the implementation technology.Peer ReviewedPostprint (published version

Bandwidth Based Methodology for Designing a Hybrid Energy Storage System for a Series Hybrid Electric Vehicle with Limited All Electric Mode

The cost and fuel economy of hybrid electrical vehicles (HEVs) are significantly dependent on the power-train energy storage system (ESS). A series HEV with a minimal all-electric mode (AEM) permits minimizing the size and cost of the ESS. This manuscript, pursuing the minimal size tactic, introduces a bandwidth based methodology for designing an efficient ESS. First, for a mid-size reference vehicle, a parametric study is carried out over various minimal-size ESSs, both hybrid (HESS) and non-hybrid (ESS), for finding the highest fuel economy. The results show that a specific type of high power battery with 4.5 kWh capacity can be selected as the winning candidate to study for further minimization. In a second study, following the twin goals of maximizing Fuel Economy (FE) and improving consumer acceptance, a sports car class Series-HEV (SHEV) was considered as a potential application which requires even more ESS minimization. The challenge with this vehicle is to reduce the ESS size compared to 4.5 kWh, because the available space allocation is only one fourth of the allowed battery size in the mid-size study by volume. Therefore, an advanced bandwidth-based controller is developed that allows a hybridized Subaru BRZ model to be realized with a light ESS. The result allows a SHEV to be realized with 1.13 kWh ESS capacity. In a third study, the objective is to find optimum SHEV designs with minimal AEM assumption which cover the design space between the fuel economies in the mid-size car study and the sports car study. Maximizing FE while minimizing ESS cost is more aligned with customer acceptance in the current state of market. The techniques applied to manage the power flow between energy sources of the power-train significantly affect the results of this optimization. A Pareto Frontier, including ESS cost and FE, for a SHEV with limited AEM, is introduced using an advanced bandwidth-based control strategy teamed up with duty ratio control. This controller allows the series hybrid’s advantage of tightly managing engine efficiency to be extended to lighter ESS, as compared to the size of the ESS in available products in the market