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UCR team’s new evolutionary-algorithm-based EMS for PHEVs can deliver >30% fuel savings than conventional controls

Engineers at the University of California, Riverside (UCR) have developed a new online energy management system (EMS) based on an evolutionary algorithm for plug-in hybrid vehicles (PHEVs) that they say can improve PHEV fuel efficiency by more than 30%. A paper describing the research was recently accepted for publication in the journal IEEE Transactions on Intelligent Transportation Systems.

PHEVs, which combine an internal combustion engine (ICE) with an electric motor and a large rechargeable battery, offer advantages over conventional hybrids because they can be charged using grid electricity, which reduces their need for fuel. However, improving the efficiency of current PHEVs is limited by shortfalls in their energy management systems (EMS), which control the power split between engine and battery when they switch from all-electric mode to hybrid mode.

The paper focuses on a power-split architecture in which the internal combustion engine (ICE) and electric motors can, either alone or together, power the vehicle while the battery pack may be charged simultaneously through the ICE.

Broadly, existing EMS for PHEVs are either rule-based or optimization-based.

  • Rule-based EMS are fundamental control schemes operating on a set of predefined rules without prior knowledge of the trip. The control decisions are made according to the current vehicle states and power demand only. Such strategies are easily implemented but the resultant operations may be far from being optimal due to not considering future traffic conditions.

  • Optimization-based EMS aim at optimizing a predefined cost function according to the driving conditions and behaviors. The cost function may include a variety of vehicle performance metrics, such as fuel consumption and tailpipe emissions.

However, notes the UCR team, most existing PHEV EMS have one or more of the following limitations:

  1. Lack of adaptability to real-time information, such as traffic and road grade. This applies to rule-based EMS the parameters or criteria of which have been pre-tuned to favor certain conditions (e.g., specific driving cycles and route elevation profiles). Most EMS that are based on global optimization off-line assume that the future driving condition is known;only a few studies have focused on the development of on-line EMS for PHEVs.

  2. Dependence on accurate (or predicted) trip information that is usually unknown a priori. Many of the existing EMS require at a minimum the trip duration as known or predicted information prior to the trip. Furthermore, it is reported that the performance of EMS is largely dependent on the time span of the trip [20]. There are very few studies analyzing the impacts of trip duration on the performance of EMS for PHEVs.

  3. Emphasis on a single trip level optimization without considering opportunistic charging between trips. The most critical feature that differentiates PHEVs from conventional HEVs is that PHEVs’ batteries can be charged by plugging into an electrical outlet. Most of the existing EMS are designed to work on a trip-by-trip basis. However, taking into account inter-trip charging information can significantly improve the fuel economy of PHEVs.

To address these limitations, we herein propose a generic framework of on-line EMS for PHEVs that uses an evolutionary algorithm (EA) to optimize vehicle fuel economy in real time. For the purpose of on-line implementation, the optimization is conducted on a sliding time window basis rather than on an entire trip basis. Meanwhile, two types of state-of-charge (SOC) control strategies (i.e., SOC reference control and self-adaptive control), which govern the utilization of vehicle battery power to achieve optimal fuel efficiency for the vehicle without the knowledge of trip duration, are proposed within the framework and compared with conventional binary control strategies.

The major contributions of this paper include: 1) development of a generic framework of on-line EMS for PHEVs; 2) exclusion of trip duration as required information for PHEVs’ energy management; 3) quantification of the performance of the proposed EMS with respect to different trip durations; and 4) consideration of the impacts due to inter-trip charging opportunities.

—Qi et al.

Flow chart of the proposed on-line EMS. Click to enlarge.

The framework consists of information acquisition (from external sources); prediction; optimization; and powersplit control. The entire trip is divided into segments or time horizons. Both the prediction and the control horizons keep moving forward (in a rolling horizon style) while the system is operating. More specifically, the prediction model is used to predict the power demand at each sampling step (i.e., each second) in the prediction horizon. Then, the optimal ICE power supply for each second during the prediction horizon is calculated with this predicted information.

Control of the vehicle’s SOC is formulated as a combinatory optimization problem that can be efficiently solved by the estimation distribution algorithm (EDA). In each control horizon, the pre-calculated optimal control decisions are inputted into the powertrain control system (e.g., electronic control unit (ECU)) at the required sampling frequency.

Using real-world data to evaluate the strategy, they found that the self-adaptive control strategy used in the proposed system statistically outperforms the conventional binary control strategy with an average of 10.7% fuel savings without considering charging opportunity and 31.5% fuel savings when considering charging opportunity.

In reality, drivers may switch routes, traffic can be unpredictable, and road conditions may change, meaning that the EMS must source that information in real-time. By mathematically modeling the energy saving processes that occur in nature, scientists have created algorithms that can be used to solve optimization problems in engineering. We combined this approach with connected vehicle technology to achieve energy savings of more than 30%. We achieved this by considering the charging opportunities during the trip—something that is not possible with existing EMS.

—Xuewei Qi, lead author

The current paper builds on previous work by the team showing that individual vehicles can learn how to save fuel from their own historical driving records. Together with the application of evolutionary algorithms, vehicles will not only learn and optimize their own energy efficiency, but will also share their knowledge with other vehicles in the same traffic network through connected vehicle technology.

Even more importantly, the PHEV energy management system will no longer be a static device--it will actively evolve and improve for its entire life cycle. Our goal is to revolutionize the PHEV EMS to achieve even greater fuel savings and emission reductions.

—Xuewei Qi

This project was supported in part by the National Center for Sustainable Transportation. The UCR Office of Technology Commercialization has filed patents for the inventions above.


  • X. Qi; G. Wu; K. Boriboonsomsin; M. J. Barth, “Development and Evaluation of an Evolutionary Algorithm-Based Online Energy Management System for Plug-In Hybrid Electric Vehicles,” IEEE Transactions on Intelligent Transportation Systems doi: 10.1109/TITS.2016.2633542



I don't want a parallel hybrid, i want a serial hybrid with a solar panel on the roof and secondary heat electric recapture. Don't buy anything till they sell a cheap convenient car doing 130 mpg on regular gas.


Solar on the roof? Do the math please before making such a statement.


"Do the math"? Are you kidding? Most people seem to have no clue about math or physics.


a typical solar panel is 1.6 x 0.8 m in size and generates about 220W.
You might get two on the roof (assuming they were curved).
Thus, say 450W.
Say 400 as it is pointing in the wrong direction.
While you drive at say 15Kw, this does not sound like much, but if you got 6 hours charging / day (parked outside), you could get 2.4 KwH or say 7.2 miles driving.
So you might save electricity worth 30-50 cents.
You would be better off with a 3Kw charger at your place of work.


Plugin Hybrids should be viewed as interim solutions until decent range batteries for fully-blown BEVs are available.


@Lad, the big advantage of a plug-in is that it needs a battery sized to average distance traveled, rather than maximum (or aiming for maximum) distance anticipated.
Thus, 12 kwH might be enough for a PHEV, while you might want 90 in a BEV.
Thus it is lighter and uses less batteries, you could make (say) 8x as many PHEVs as BEVs for the same amount of batteries.
If 90% of your driving is on electric, you hardly need a full BEV.
The "only" problem is cost and complexity, but this will be reduced as the manufacturers become more familiar with PHEVs.


That is comparable to the best results achievable by
the many reported hypermiling results while not upsetting traffic flow or breaking road rules.
(an optional override may be a popular hack?)

These strategy will give an important e advantage for bevs as well.

Always better to keep expensive vehicles from sun and rain under cover with fixed panels but where that's not possible there are still some useful stationary applications.
Battery tenders, communications equipment, air circulation...
Cheap solar options such as paints glass etc will eventually be developed.



I think that you are being a bit optimistic. I measured the roof of a typical hatch back and came up with 1.2 x 1.8 meters. If you use a solar cell efficiency of 18% and a solar flux of 1 KW/m2 (This is at the equator so this is really too much) you have about 388 watts but given a flat panel and a latitude of 40 deg (Kansas City) plus the sun sweeps thru an angle of -45 to +45 over 6 hours, you need to multiply this by the cosine of 52 deg (an optimistic guess as I am too busy to try to do the required integration). So you have an optimistic 240 watts or about 1.4 KW hr for 6 hrs. The Chevy Volt has 18 KW hr and gets about 57 miles so you might pick up about 4.4 miles range


May be some day car solar roof will cost nothing. Then it will be reasonable to have it.
I would prefer to calculate truck trailer solar roof. In case first electric truck on the road it could make some impact. But in any case those things shall become much more cheaper.



With a US 53 ft long x 8.5 ft wide trailer, you have about 40 sq meters so you might get about 4.5 KW or about 6 hp. The trucks are probably using an average of at least 200 hp or 150 KW so you are not going to get far on 4.5 KW which is about 3% of the required power.


@ sd:
53'= 13.462m; 8,5'= 2.159m or 13.462m * 2.159m = 29m²
A current high tech. panel (Panasonic) yields ca. 220 W/m²
Total power is ca. 0.22 kW/m²* 29 m²= 6.38 kW/hr * 6 hrs = 38.3 kWh and may suffice for 1 hr of truck driving.


@sd, I was optimistic, but not by much.

The main advantage would be a few (1.5-2.5) KwH for daytime charging without a plug in point.

You'd probably be better building a charging car port with say 5 or 6 panels and just charge the car or feed the grid.

Car shapes are not good for solar panels: 2 dimensional curves - a solar carport would be much better - flat, can be tilted south.

Also, putting a big black solar panel on top of a car in a sunny place might make if very warm inside.
I am not advocating solar on cars, I was just "doing the math".


Yoatmon: Your calculations have some problems

53' x 0.3048 = 16.1544 m
8.5 x 0.3048 = 2.5908 m

I rounded off a bit and took 16 m x 2.5 m = 40 m2

I took a solar irradiance of 1KW/m2 and 18% solar cell efficiency but I will use 22% and give you 220 w/m2. This is probably optimistic but I do not know how Panasonic did their measurements. Anyway, this would give you 8.8 KW. However, as the solar cells are not normal to the sun unless you are at the equator on the equinox at high noon, you need to correct for the angle of the sun. I took an angle of 40 degrees latitude and as the sun swings thru a -45 to +45 over 6 hrs I took a scientific wild ass guess of an average of 52 degrees off normal (which is probably a bit optimistic). So you need to correct by the cosine of 52 or 0.62. To get the correct answer you need to integrate over compound angle). See if you want more on this. So now you are down to 5.4 KW or about 32.5 KWhr over 6 hours. But the problem is that most tractors are running about 450 hp or 340 KW. I took a very liberal average power usage of 150 KW but something over 200 KW would probably be a better number. Some of the drivers that are running 80 mph (legal limit in a number of western states) are probably pushing the engine to max and maybe running closer to 550 hp or over 400 KW. Anyway, you would be very lucky to get 10 minutes of driving from this arrangement.

Brent Jatko

"Don't buy anything till they sell a cheap convenient car doing 130 mpg on regular gas."

IOW, don't buy anything, ever?


Batteries and solar cells are not ready large trucks. A 3X to 5X improvement is required.

Meanwhile, FCs are capable of doing it (now) for large trucks, buses and passenger trains.

FC powered twin car articulated 300 passenger, 140 kph, 500 Km extended range trains will be in operation in Germany by December 2017. Range could be 2X to 5X with large H2 tanks.

Alstom will supply the trains,, H2 stations and maintenance.

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