Under the global voice of “energy saving” and the current boom in the development of energy storage technology at home and abroad, energy optimal control of the whole hybrid electric vehicle power system, as one of the core technologies of electric vehicles, is bound to become a hot target of “clean energy” vehicle development and research. This paper considers the constraints to the performance of energy storage system in Parallel Hybrid Electric Vehicle (PHEV), from which lithium-ion battery frequently charges/discharges, PHEV largely consumes energy of fuel, and their are difficulty in energy recovery and other issues in a single cycle; the research uses lithium-ion battery combined with super-capacitor (SC), which is hybrid energy storage system (Li-SC HESS), working together with internal combustion engine (ICE) to drive PHEV. Combined with PSO-PI controller and Li-SC HESS internal power limited management approach, the research proposes the PHEV energy optimal control strategy. It is based on revised Pontryagin’s minimum principle (PMP) algorithm, which establishes the PHEV vehicle simulation model through ADVISOR software and verifies the effectiveness and feasibility. Finally, the results show that the energy optimization control strategy can improve the instantaneity of tracking PHEV minimum fuel consumption track, implement energy saving, and prolong the life of lithium-ion batteries and thereby can improve hybrid energy storage system performance.
In 2015, the incident that the illegal use of emissions control software of Volkswagen further triggers a strong concern on cars “energy saving” problem. So it is essential to use energy storage technologies to alleviate energy waste. Considering the key factor that restricts battery performance and service life in lithium-ion battery, this paper applies Li-SC HESS to PHEV. However, how to coordinate each of storage units charging/discharging and optimize energy management of vehicle power system in real time is the key to implement the performance optimization of Li-SC HESS and minimize fuel consumption in PHEV. Santucci et al. [
In this paper, PMP global optimization control algorithm has been adopted, which combines with Li-SC HESS internal power limited management strategy, thus taking an energy optimal control to PHEV, having an optimal management of lithium-ion battery charging/discharging states, improving the Li-SC HESS performance, and meanwhile ensuring that the vehicle fuel consumption during running can track the fuel consumption minimum trajectory in real time.
According to vehicle power-train structure, HEV can be divided into SHEV, PHEV, and S-PHEV, wherein the SHEV control system is not considered because of its relatively simple control and its large energy conversion, which easily poses a threat to lithium-ion batteries life. PHEV can make energy more efficient and fuel economy relatively higher, so in order to reduce fuel consumption as much as possible this paper selects PHEV power-train structure, with its power-type composition architecture being shown in Figure
Vehicle Structure of PHEV.
Power flow schematic of PHEV power system.
From Figure
The vehicle power flow of PHEV power system is shown in Figure
As PHEV energy storage device, Li-SC HESS owns its control module which is also one part of the whole vehicle control. Selecting Li-SC HESS appropriate equivalent circuit model, which includes its topology, the equivalent circuit model of each storage element, and control variables, is the precondition for the study on PHEV power system energy optimization control strategy. When the vehicle is in state of accelerating or moving uphill, this structure can quickly respond to the demand of alternator’s high instantaneous power and it can also recover energy when the vehicle is in state of decelerating and braking. Besides, with respect to the topology structure between lithium-ion batteries and SC, each Li-SC HESS topology will make a difference in its component parts, different practical applications, and different connections, like the 4 kinds as follows: SC and lithium batteries parallel directly, SC and lithium-ion batteries parallel through each independent DC/DC converter, lithium-ion batteries (/SC) connects to DC/DC, and then parallel with SC (/lithium-ion batteries). Considering the advantages of HESS combination type, energy conversion efficiency, the complexity of system structure, and others, SC connects to DC/DC converter and then parallels with lithium-ion batteries (Figure
The topology of Li-SC HESS.
This paper selects first-order RC parallel circuit as lithium-ion battery equivalent model (Figure
Lithium-ion battery equivalent model based on first-order RC parallel circuit.
Under different road conditions, the current will change dramatically with different power demands of the alternator; environmental factors such as battery temperature will also be affected, thus forming a threat to the lithium-ion battery life and safety. From Figure
From (
From (
Similarly, the instantaneous power
Similarly, considering the structural flexibility and lower computing costs, choosing the equivalent first-order RC parallel circuit structure as SC equivalent model, like Figure
SC equivalent model based on first-order RC parallel circuit.
From Figure
In response to the development goals of green energy economy, it should make better performance of Li-SC HESS, minimizing ICE energy consumption, reducing economic costs, and reducing environmental pollution. This paper makes ICE minimum energy consumption as a control target variable. Throughout the drive cycle
PHEV energy optimal management requires considering the restrictions of the objective function from a global point of view, mainly from vehicle structure constraints; both physical model constraints of ICE and alternator and Li-SC HESS state constraints.
Designing the rational energy optimal control strategy usually regards the vehicle driving force and vehicle speed as the given system status conditions, which are denoted as
From (
ICE is a complex system; many of its physical phenomena are not easy to be modeled, like the burning process. In this case, the research ignores the temperature dependence of ICE and its dynamic characteristics, and then get the distribution graph of instantaneous fuel consumption function under the action of
Distribution graph of instantaneous fuel consumption function under the action of
Graph of Alt. efficiency function curve under the action of
Graph of Alt. maximum current curve under the action of
As it can be seen from Figures
Formula (
Among energy storage element, SOC is an important parameter of overcharging/overdischarging and cycle-life of storage elements. According to Li-SC HESS equivalent mathematical model, in order to minimize the charging/discharging times in the certain drive cycle,
Since lithium-ion battery and SC are all energy buffer devices, in the continued charging state, assessing fuel economy of the energy optimization control, PMP algorithm should meet the need of the end constraints conditions of
With the consumption function
From (
From (
According to Hamiltonian function equation (
From (
From (
Although the costate variable initial value
Considering
PSO-PI real-time optimization “
From (
From (
The main steps of PSO-PI controller parameter optimization are as follows: Assuming that the particle Update the Compare Similarly, compare Judge the termination constraints of PSO algorithm; if it is terminated, go directly to step Output the optimized parameter values
Since PI controller is not adaptive itself, add PSO algorithm to adjust the parameters of the controller; the self-adaptability is improved to achieve the purpose of fast tracking and controlling the covariable in PMP algorithm. When group scale is set to 30, the maximum calculation period to is set to 100, and both
The convergence curve of the best individual fitness function.
Above, the research takes the vehicle dynamic character and minimal fuel consumption as the main analysis object and initially establishes energy optimization management method of PHEV power system. Although the allocated processing factors can ensure the coordinated allocation of power between lithium-ion battery and SC, SOC constraints during controlling just to prevent Li-SC HESS overcharge and overdischarge, which are the basic conditions. In order to further improve Li-SC HESS performance, it needs to make a real-time management of the power of Li-SC HESS each energy storage unit during the charging/discharging state. The vehicle energy optimization control flow chart is shown in Figure
The overall flow chart of PHEV energy optimization control.
According to the lithium-ion battery’s characteristics of low power density, strong energy density, and limited life, the research adopts the preresponse principle of SC when the demanded power of the alternator changes and dictates that when
PHEV with Li-SC HESS in this paper is obtained by the secondary development of PHEV model based on ADVISOR software (Figure
PHEV simulation model.
Taking into account of the majority of domestic small car users daily and mainly using in the city, the research adopts the urban road cycling conditions (CYC-UDDS). The real-time curve of driving cycle speed is shown in Figure
(a) Under CYC-UDDS, real-time curve of driving cycle speed. (b) Under CYC-UDDS, gear position curve of the driving cycle.
(1) The comparison results of PHEV power system before and after: when working normally in the vehicle driving cycle, Li-SC HESS can provide or absorb some of the energy through alternator, reducing fuel consumption ICE. Figures
(a) Before PMP energy optimization algorithm. (b) After PMP energy optimization algorithm.
Comparing Figure
(2) The result of real-time optimization of output coefficients by PSO algorithm: in order to demonstrate the characteristic of real-time tracking by PSO-PI controller, the research obtains the output coefficient
Output coefficient curve of real-timely optimized Hamiltonian function by PSO-PI controller.
From Figure
The simulation situation between the single lithium-ion battery energy storage and Li-SC HESS. It can be known from Figures
(a) SOC curve of a single lithium-ion battery energy storage. (b) SOC curve of Li-SC HESS.
(a) Current curve of a single lithium-ion battery energy storage. (b) Current curve of Li-SC HESS.
The research designs a kind of PHEV that introduces Li-SC HESS. Compared with traditional vehicles, This PHEV has the advantages of both ICE and Li-SC HESS. For example, the internal ICE can use existing gas station resources and reduce the overall investment costs. Meanwhile, it can alleviate the difficulty more effectively than pure electric vehicles when solving the problems brought from defrosting, air conditioners, and other pieces of large energy consumption equipment. Li-SC HESS can help extend battery life and extend the driving ranges of cars. In particular, the embedment of SC makes Li-SC HESS well suited to start the vehicle, the speed change, and energy recovery during braking. Mainly, PHEV energy optimization control strategy can effectively reduce vehicle exhaust emissions, benefit for the urban environment, which has a high research value.
The authors declare that they have no competing interests.
The research group would like to thank the “Research on Electric Vehicle Li-ion battery and SC Hybrid Energy Storage System Energy Management Strategy” (Grant no. 51677058) for funding this research.