June 2008 Newsletter

by Gordy Slack

 

Squeezed by the four-dollar gallon of gas, the threats of climate change, and the dependence on foreign oil, American engineers are searching in new fields for more ways to wring more and cleaner miles out of a growing variety of fuels. One of the most promising recent innovations is the Homogeneous Charge Compression Ignited (HCCI) engine, which combines the efficiency and versatility of diesel engines with the cleanliness of spark-ignition engines. Currently, spark-ignited gasoline engines burn relatively cleanly but not very efficiently. And today’s best diesels are quite efficient, but tend to emit lots of particulates, especially the dreaded NOx.

 

HCCI engines, however, use 15 percent less fuel than gas engines and emit only 30 percent of the NOx of a typical diesel engine. Thus, they appear to combine the best of both engines. Except for one problem: temperature variations. In the words of UC Berkeley engineering post-doc and biofuel specialist Hunter Mack, “Temperature variations can make HCCI engines a nightmare on wheels.”

The way that HCCI engines work is to premix fuel the way that a spark engine does, but then compression-ignite the fuel in the manner of a diesel engine. It is the compression ignition that gives them their high efficiency but also leaves them vulnerable to temperature variations across the cylinders. The ignition occurs when pressure reaches a certain point within a cylinder, and that point is achieved sooner if temperatures are higher. So, if a load changes on the engine and the coolant gets hotter as it moves through, then the coolant will not thoroughly cool some cylinders, which will cause the ignitions to fall out of synch and misfire. Suddenly, what was a very efficient engine starts to lose power, suck fuel, and spew pollutants.

“These HCCI engines have a lot going for them,” says UC Berkeley engineer Robert Dibble. “They are clean, efficient, and can run on almost anything— including a variety of biofuels, diesel, or gasoline-like mixtures—but before we can really exploit them, we have to solve this [temperature] problem.”

The HCCI engines need to have control, which means they must be properly sensed, evaluated, and then actuated, according to Dibble. In order for these engines to be practical, as their load becomes uneven, each HCCI cylinder has to be monitored and adjusted constantly.

To be efficient, these cylinders need to communicate with each other and coordinate their actions. With support from CITRIS, Dibble is working to make that happen. He and his collaborators are developing sensors and controllers that will keep temperatures constant throughout the engine or compensate for temperature differences by adjusting pressure ratios within the cylinders.

Creating the algorithms to coordinate the firing of cylinders is tricky, notes Mack. “Different cylinders at different temperatures may have only a one percent difference in their compression ratios, but when they are compressing something 20 times, that difference is greatly amplified,” Mack explains. “There are a number of other factors that affect combustion timing too: the fuel-to-air ratio, charge stratification, intake pressure, and a host of other factors need to be monitored and adjusted in order to maximize the power and efficiency. So, this is a multi-variable problem that needs to be solved rapidly.”

Albert Pisano, professor and chair of UC Berkeley’s Department of Mechanical Engineering, is developing wireless sensors that will make the essential communication step possible. Some may be microphones, others will sense temperature or pressure, but many times a second they will report on conditions from inside the cylinders. Once the engine knows that some cylinders have to be a little hotter or cooler or slower or faster to fire in synch with their neighbors, it will take steps to re-adjust them.

While Pisano’s forté is building robust sensors and Mack’s expertise is drawing conclusions from the data they provide, Dibble’s challenge is making the engine act quickly and properly based on the information that it receives. Exhaust, for instance, may be redirected to heat up cooler parts of the engine. Dibble compares the regulation to a water fixture in the shower that can automatically microadjust the ratio of cold water to hot in order to keep the shower’s temperature just right, even if someone has started a load of laundry nearby.

Though the timing issue is HCCI’s biggest problem to be conquered, the Berkeley team is not stopping there. In addition, they are designing wireless relationships for the car that go beyond the engine’s own parts. One of HCCI’s great qualities is its ability to run on a variety of fuels. While diesel engines cannot use gasoline, or gasoline engines use diesel fuel, HCCI engines can run on both types and on a wide range of biofuels as well. Dibble and UC Berkeley engineering professor Van Carey have been talking to oil companies about establishing and taking advantage of wireless communication links between the vehicle and the fuel pump. “The car can pull up to the station and tell the pump that its efficiency is low, for instance,” says Carey. “And the pump responds, perhaps by determining that the engine is having incomplete combustion and needs a higher octane fuel. The pump could also recommend the cheapest, best-running biofuel cocktail available at that time.”

“Fuel does not usually have much brand appeal,” says Mack. “But these fuels would be mixed specifically for your car; the microbrews of gasoline.”

The conversation between the car and the service station could go much further than the subject of fuel. Wireless sensors could also report to the station on the state of the car’s oil, coolant, brakes, air filter, tire pressure, and fan belts, says Carey. Such an instant and effortless diagnostic would keep cars running at their safest and most efficient. And best of all, these sensors would work for any vehicle with something worth talking to the gas station about, not just those with HCCIs.

“Not long ago, when gas only cost people two dollars a gallon, the idea of tailoring your fuel to the car would have seemed over the top,” says Dibble. “But imagine a year from now when gas has continued to skyrocket in price,” he said. “If I tell you that with my HCCI engine and properly-tuned fuel I could increase your fuel economy by 20 percent, you are going to sit up and listen.”

 

by Gordy Slack

California's Great Central Valley is the ideal place to develop the large-scale concentrator-type solar technology that can make a real difference in the U.S. energy crisis. There is plenty of space here, lots of sun, and only a little cloud cover. And the peak demand for energy in the middle of the day—to run air conditioners—coincides with the peak availability of energy-producing photons from the sun. Central Valley residents consume a lot of energy themselves, but there are several large urban areas close enough to benefit from power generated here. Carlos Coimbra, associate professor in the School of Engineering at UC Merced, believes that, within 15 years, solar concentrators could produce as much as 15 percent of all the energy consumed in California.

But there is one frustrating obstacle to this promising scenario: our inability to predict reliably the amount of direct solar irradiance available to the state’s energy grid at least a day or two in advance. Without that, notes Coimbra, utility companies simply cannot risk relying on this highly productive breed of collectors to produce the energy that they need to deliver.

Even a small oscillation—just 2 percent up or down in the energy grid—can cause the whole system to shut down, Coimbra says. Today, the California grid remains stable on the supply side because it is powered by very predictable fuel and hydroelectric sources. The only fluctuation is in demand: if there is a heat wave and everyone turns on their air conditioner at the same time, then there can be problems. But those demand-side fluctuations can be addressed by the reliable, albeit extreme measure of rolling blackouts. However, if the grid depends on a lot of its energy coming from solar concentrators on a given day, but the solar rays are unexpectedly blocked by aerosol or cloud cover, then the power supply can dip and take out the whole grid.

“We can put whatever money we want into solar,” Coimbra says, “but if we cannot predict direct normal irradiance for the next 24 hours, then we cannot hook these things into the grid. This is a real bottleneck.”

Direct Normal Irradiance (DNI) is the solar engineer’s term for the radiation that comes straight from the sun onto a given area. (“If you look at the sun through a paper towel tube, the rays hitting your eye are the DNI,” says Coimbra.) Much of the light we live by is not direct, but diffused, buffeted around by the atmosphere, and reflected off of the ground, buildings, and water. Although that diffused irradiation still contains energy that can be exploited by some solar technologies, it is of little use to concentrators, which rely mainly on DNI for their high efficiency.

While meteorologists are able to predict on Monday what overall sunlight— global solar irradiance (GSI)—will be available on Tuesday, they are not able to predict DNI because of the many variables that can influence it. Cloud cover has the biggest impact on DNI, but aerosol content, water vapor, carbon dioxide, and ozone all diffuse DNI too.

Last year, CITRIS gave Coimbra $75,000 to run a one-year proof-of-concept project called the Solar Irradiance Mapping Initiative (SIMI). The project is a collaboration between professors Coimbra and Qinghua Guo at Merced and Jean-Pierre Deplanque at UC Davis. The researchers will set up two experimental solar stations, one on each campus, that are equipped with highly-sensitive instruments that can independently measure DNI, GSI, and the total combination of the two (called local global irradiance.) The solar data collected at those ground stations will be correlated with several kinds of satellite image data—on weather, aerosol and ozone content in the atmosphere, and other variables—as well as ground radar information about local atmospheric conditions.

Using an approach to complex statistical associations called genetic algorithms, Coimbra will process all of that data into an increasingly accurate and predictive model. Genetic algorithms borrow concepts from the biological processes of mutation and natural selection to “evolve” mathematical “genes” that “constantly evolve and improve and adapt to different conditions,” says Coimbra. “It is a perfect application for a highly stochastic situation like this.”

If the Davis and Merced ground observatories generate the kinds of associations Coimbra expects them to, they will serve as a model for a much wider network of ground stations that could be distributed across the state, eventually creating a kind of real-time and short-term predictive geographical information system (GIS) that maps for solar irradiance. The ground stations will be used to benchmark the models developed for analyzing geo-stationary satellite and radar images, which in turn will map DNI availability throughout the state. Guo is an expert in GIS. At first, the information provided by such a system would be a key tool for both utilities and for policy makers trying to set up rational and reliable networks of sustainable energy sources that rely on solar irradiance, including concentrator technologies and, perhaps, wind turbines too. “Wind is just another kind of solar energy,” says Coimbra.

Because even small oscillations in the supply side can take down the entire grid, the predictions needs to be very accurate, says Coimbra. Gathering the wide range of data sets that independently measure GSI, DNI, and local global irradiance and then studying it for relationships can unveil less-than-obvious but very helpful associations that will boost the utilities' confidence predicting DNI.

Armed with the ability to forecast accurately, utility companies and policy makers will be able to invest confidently in California’s abundant solar energy opportunities, says Coimbra. And as the growing economic and environmental price of fossil fuels makes prices for those clean and renewable energies more and more competitive, the time is ripe for these technologies.

“California’s Central Valley may be the best place to have solar power in the U.S. Theoretically, we could build 300-megawatt power plants all over the Valley. But no one is going to support a high percentage of the grid being solar until these short-term predictions can be made on a reliable and systematic basis,” says Coimbra.

“It is not too often a researcher has the opportunity to remove a major bottleneck to an important viable technology. Concentrator technology is available, but it is not yet completely viable…not without the piece that we are trying to provide here. That, for me, is a huge motivation,” says Coimbra.